Jobs Data Engineer

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

RESPONSIBILITIES

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

DESIRED SKILLS

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines(e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Senior Software Engineer to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform's performance and scalability boundaries across all major clouds.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

RESPONSIBILITIES

• Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers.
• Write and review high-quality, performance-critical code in Java and/or C++.
• Own end-to-end delivery of features from technical design through production rollout.
• Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths.
• Integrate deeply with columnar formats, open table formats, and connectivity drivers.
• Mentor middle engineers, lead code reviews, and set technical standards for the team.
• Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker).
• Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O.
• Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued.
• SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation.
• Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components.
• CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes.
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and rigorous code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.

DESIRED SKILLS

• Deep experience with Apache Arrow (columnar in-memory format).
• Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework).
• Experience with Gandiva or LLVM-based expression compilation and code generation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design.
• Prior experience contributing to open-source data infrastructure projects.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Middle-level SDET to design and maintain automated tests for a large-scale distributed data platform. You will validate the correctness, performance, and reliability of the query engine, connectivity layer, and backend services across all major clouds.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

RESPONSIBILITIES

• Develop and maintain automated tests in Python / pytest for backend services, REST APIs, and distributed data components.
• Write end-to-end, integration, and regression tests covering SQL query execution, data correctness, and platform APIs.
• Support performance and load testing with JMeter, including workloads over JDBC / ODBC / Arrow Flightdrivers.
• Validate data-intensive scenarios — query plans, result correctness across data sources, metadata consistency, and behavior under concurrency.
• Contribute to CI/CD test pipelines in Jenkins — configure, maintain, and troubleshoot.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Investigate failures across the stack — query engine, distributed services, drivers, infrastructure — and drive them to resolution with engineering.
• Collaborate with US-based developers on testability and quality gates.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with a solid grasp of OOP and software design principles.
• SQL & Data: Strong SQL skills and solid understanding of how relational and analytical data systems work.
• Data-intensive testing experience: Hands-on experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 3+ years in backend/system test automation or SDET roles.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and deploying/maintaining test environments.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

DESIRED SKILLS

• Experience testing REST APIs and backend microservices at scale.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines(e.g., Presto, Trino, or similar).
• Understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours:EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

ABOUT THE CLIENT

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

ABOUT THE ROLE

We are looking for a Senior SDET to lead the design of automated test frameworks and testing strategy for a large-scale distributed data platform. You will own the quality of the query engine, connectivity layer, and backend services end-to-end — from framework architecture through CI/CD infrastructure across all major clouds — and mentor middle engineers on the team.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

RESPONSIBILITIES

• Architect, design, and evolve automated test frameworks in Python / pytest for backend services, REST APIs, and distributed data components.
• Define testing strategy for new features and platform components — coverage, risk assessment, and quality gates.
• Own end-to-end, integration, performance, and regression testing covering SQL query execution, data correctness at scale, and platform APIs.
• Lead performance and load testing efforts with JMeter, including workloads over JDBC / ODBC / Arrow Flightdrivers.
• Design and validate large-scale data testing scenarios — query plans, result correctness across heterogeneous data sources, metadata consistency, and behavior under high concurrency.
• Own CI/CD test pipelines in Jenkins — architect, maintain, and continuously improve.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker; drive automation and reproducibility.
• Investigate complex, cross-layer failures and drive root-cause analysis with engineering.
• Mentor middle SDETs, review test designs, and set quality standards across the team.
• Partner with US-based development leads on shift-left practices, testability, and release readiness.

REQUIRED QUALIFICATIONS

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with deep understanding of OOP, software design principles, and test framework architecture.
• SQL & Data: Advanced SQL skills and strong understanding of relational and analytical data systems, including query execution internals.
• Data-intensive testing experience: Demonstrated experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 5+ years in backend/system test automation, with demonstrated ownership of test strategy and infrastructure.
• CI/CD & DevOps: Solid experience architecting and maintaining Jenkins pipelines and test environments.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes (running workloads, debugging pods, deploying complex environments).
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, defining test strategy, or leading a QA/SDET function.

DESIRED SKILLS

• Deep experience testing REST APIs and backend microservices at scale.
• Hands-on with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines(e.g., Presto, Trino, or similar).
• Strong understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools at production scale.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Deep understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Prior experience leading a QA/SDET function in a data-platform or database engineering environment.
• Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

Dataforest is looking for a Data Engineer to join an interesting software development project in the field of Cybersecurity. Our client’s platform offers Identity Insights drives real-time, multi-contextual digital forensics to protect new account opening workflows and expose fake accounts already in a customer database.

You'll be a great fit if you have:

- 3+ years of hands on in data engineering;
- 3+ years of commercial experience with Python;
- Advanced experience with SQL DBs (optimisations, monitoring, etc.);
- Advanced experience with PySpark;
- Solid understanding of ETL principles (architecture/ monitoring/ alerting/search and resolve bottlenecks);
- Familiar with AWS infrastructure (boto3, S3 buckets, etc);
- Experience working with large volumes of data;
- Understanding the principles of medallion architecture.

Would be a plus:

- Cassandra/Scylla
- PostgreSQL
- Pandas
- Experience with Kafka and Redis

What you'll do:

- Maintain data processing architecture using Python and PySpark that interacts with ScyllaDB & PostgreSQL.
- Work with Databricks infrastructure to ensure reliability, scalability, and cost efficiency.
- Proactively identify bottlenecks and suggest technical improvements.

We ensure your growth with:

- Working in a fast-growing company;
- Great networking opportunities with international clients, challenging tasks;
- Personal and professional development opportunities;
- Competitive salary fixed in USD;
- Paid vacation and sick leaves;
- Flexible work schedule;
- Friendly working environment with minimal hierarchy;
- Team building activities, corporate events.

Are you passionate about building cutting-edge, AI-ready data platforms from the ground up? We are looking for a Senior Data Engineer to join our Data Engineering Team and lead high-impact, greenfield initiatives.

You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure.

In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines — turning architectural concepts into production-grade solutions.

Responsibilities:

• Design and build scalable, cloud-native data platforms from greenfield to production
• Implement near-real-time ingestion pipelines using event-driven patterns
• Define and enforce platform standards, including Data Lake / Lakehouse principles, medallion architecture, and data contracts
• Refactor and optimise existing Spark and PySpark scripts for performance and maintainability
• Introduce best practices for code quality, testing, and CI/CD across data pipelines
• Drive adoption of AI tooling and agentic workflows within the data engineering team
• Ensure data quality, observability, and reliability across all pipelines and platforms

• Develop self-service tooling and microservices to simplify platform usage for other teams

   

Requirements:

• 5+ years of professional experience in Data Engineering
• Strong Python and SQL development skills for pipeline development and optimisation
• Proficiency in Apache Spark / PySpark, including query optimisation and performance tuning
• Hands-on experience with Databricks 
• Experience with at least one major cloud provider: Azure (preferred), AWS, or GCP
• Experience with stream processing technologies (Kafka, Spark Structured Streaming)
• Solid understanding of ETL/ELT patterns, data modelling (dimensional, Data Vault), and data warehousing
• Experience with orchestration tools (Apache Airflow, Azure Data Factory, or equivalent)
• Knowledge of Infrastructure as Code (Terraform or equivalent)
• Understanding of production-grade system requirements: reliability, scalability, observability, and performance

• Upper-Intermediate English level

   

Will be a plus

• Familiarity with RAG pipeline design and LLM integration patterns
• Knowledge of data governance frameworks and tools (Unity Catalog, Apache Atlas, or similar)
• Experience with dbt for data transformation and modelling

• Familiarity with MLflow, Feature Stores, or ML platform integration

   

Personal profile

• Self-driven and proactive in identifying improvements
• Comfortable working in a fast-paced, innovative environment
• Strong problem-solving mindset with attention to detail
• Open to experimenting with emerging technologies and approaches

_____________________________________________________________

Ти захоплюєшся створенням передових, AI-ready дата-платформ з нуля? Ми шукаємо Senior Data Engineer, щоб ти приєднався(-лася) до нашої команди Data Engineering та очолив(-ла) масштабні, інноваційні ініціативи з нуля.

Ти працюватимеш над побудовою сучасних хмарних дата-платформ, міграцією локальних (on-premises) легасі-систем у хмару та створенням архітектурного фундаменту для AI-ready дата-інфраструктури.

У цій ролі ти тісно співпрацюватимеш з командами Machine Learning, Data Science та Product, виступаючи ключовим технічним експертом та лідером думок. Також ти вестимеш R&D-роботи над agentic AI-архітектурами, подієво-орієнтованими системами та LLM-ready дата-пайплайнами — перетворюючи архітектурні концепції на готові до продакшену рішення.

Обовʼязки:

• Проєктувати та створювати масштабовані, хмарні дата-платформи від концепції до продакшену
• Реалізовувати пайплайни для майже реального часу (near-real-time ingestion) з використанням подієво-орієнтованих патернів
• Визначати та впроваджувати стандарти платформи, включно з принципами Data Lake / Lakehouse, медальйонною архітектурою та дата-контрактами
• Рефакторити та оптимізувати наявні скрипти на Spark та PySpark для підвищення продуктивності та зручності підтримки
• Запроваджувати найкращі практики якості коду, тестування та CI/CD для дата-пайплайнів
• Сприяти впровадженню AI-інструментів та agentic-підходів у команді дата-інженерів
• Забезпечувати якість, спостережуваність (observability) та надійність усіх пайплайнів і платформ

• Розробляти self-service інструменти та мікросервіси, що спрощують використання платформи іншими командами

   

Вимоги:

• 5+ років комерційного досвіду в Data Engineering
• Сильні навички розробки на Python та SQL для створення та оптимізації пайплайнів
• Впевнене володіння Apache Spark / PySpark, включно з оптимізацією запитів та налаштуванням продуктивності
• Практичний досвід роботи з Databricks (бажано) 
• Досвід роботи з принаймні одним великим хмарним провайдером: Azure (бажано), AWS або GCP
• Досвід роботи з технологіями потокової обробки даних (Kafka, Spark Structured Streaming)
• Глибоке розуміння ETL/ELT-патернів, моделювання даних (dimensional, Data Vault) та побудови дата-складів
• Досвід роботи з інструментами оркестрації (Apache Airflow, Azure Data Factory або аналогами)
• Знання Infrastructure as Code (Terraform або аналогів)
• Розуміння вимог до продакшен-рішень: надійність, масштабованість, спостережуваність, продуктивність

• Рівень англійської — Upper-Intermediate

   

Буде плюсом:

• Знайомство з проєктуванням RAG-пайплайнів та патернами інтеграції LLM
• Знання фреймворків і інструментів для data governance (Unity Catalog, Apache Atlas або подібних)
• Досвід роботи з dbt для трансформації та моделювання даних

• Знайомство з MLflow, Feature Stores або інтеграцією з ML-платформами

   

Особистий профіль:

• Самомотивованість та проактивність у пошуку покращень
• Комфортна робота у швидкому та інноваційному середовищі
• Сильне аналітичне мислення та увага до деталей
• Відкритість до експериментів з новими технологіями та підходами

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.
We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client looking for a Platform Engineer to drive critical infrastructure initiatives across our backend systems, with primary ownership of our core platform.
This is a high-impact role where you'll architect scalable solutions that serve our entire engineering organization - core platform services that power our AI editing capabilities.
You'll have the opportunity to shape technical decisions across multiple domains while ensuring our platform systems are robust, reliable, and optimized for growth.

Key Requirements:
🔹 5+ years of experience as a Backend Engineer, with experience building platform services or shared infrastructure;
🔹 B.Sc in Computer Science, Software Engineering, or a related field from a well-known university;
🔹 Proven expertise in backend server development, using languages like Python, Scala, Go, or Java;
🔹 Solid understanding of system design principles, API architecture, and service-oriented architectures;
🔹 Proficiency with AWS services and cloud-based architectures;
🔹 Excellent communication skills for collaborating across engineering, product, and operations teams;
🔹 Proactive mindset, having the will and ability to find areas where optimizations can benefit the entire org;
🔹 English – Upper-Intermediate or higher.

What you will do:
🔹 Drive platform-level initiatives that improve scalability, reliability, and developer experience across our backend systems;
🔹 Collaborate with multiple departments to support new platform features and technical initiatives;
🔹 Monitor platform health, investigating and resolving incidents and reliability issues;
🔹 Develop and optimize shared platform services, APIs, and infrastructure used across engineering teams;
🔹 Create internal tools and frameworks that improve developer productivity and system reliability;
🔹 Drive initiatives to improve observability, monitoring, and operational excellence across our infrastructure;

Interview stages:
🔹 HR Interview;
🔹 Tech interview;
🔹 Client Interviews;
🔹 Reference check;
🔹 Offer;

Your future responsibilities:

• Develop and maintain scalable ETL/ELT processes for data collection, transformation, and loading
• Design and implement robust data pipelines for real-time and batch data processing
• Ensure data quality, consistency, and availability for analytical and operational systems
• Optimize query performance and database architecture
• Automate the deployment and monitoring of data infrastructure components
• Work closely with analytics, development, and business teams to implement data-driven solutions

Your experience and skills:

• 2+ years of relevant experience in data engineering
• We expect you to have solid commercial experience with Python, Groovy
• Deep knowledge of Apache NiFi and hands-on experience in building and administering complex data flows
• Proficient in PostgreSQL, understanding of architecture, experience in query optimization and data schema design
• Experience with Apache Kafka, building real-time data pipelines

Will be a plus:

• Experience with Apache Airflow, workflow organization, monitoring and automation
• Working with Apache Spark frameworks for distributed big data processing
• Experience with AWS Athena and S3, interactive query services
• Experience with Apache Iceberg, understanding of modern table formats for data lakes
• Experience with Kubernetes, containerisation and service orchestration

We offer what matters most to you:

• Competitive salary: we guarantee a stable income and annual bonuses for your personal contribution. Additionally, we have a referral reward program for attracting new colleagues to Raiffeisen Bank
• Social package: official employment, 28 days of paid leave, additional “maternity leave” for fathers, and financial assistance for parents upon the birth of children
• Comfortable working conditions: the possibility of a hybrid work format, offices equipped with shelters and generators, provision with modern equipment
• Wellbeing program: all employees have access to medical insurance from the first working day; consultations with a psychologist, nutritionist or lawyer; discount program for sports and shopping; family days for children and adults; massage in the office
• Learning and development: access to over 130 online educational resources; corporate training programs, online library, mentoring program
• A great team: our colleagues are a community where curiosity, talent and innovation are welcomed. We support each other, learn together and grow. You can find like-minded people in over 15 professional communities, reading or sports clubs
• Career opportunities: we encourage advancement within the bank between functions
• Innovation and technology. Infrastructure: AWS, Kubernetes, Docker, GitHub, GitHub actions, ArgoCD, Prometheus, Victoria, Vault, OpenTelemetry, ElasticSearch, Crossplain, Grafana. Languages: Java (main), Python (data), Go (infra, security), Swift (IOS), Kotlin (Andorid)Datastores: Sql-Oracle, PgSql, MsSql, Sybase. Data management: Kafka, AirFlow, Spark, Flink, we develop expertise in AI and actively integrate it into processes
• Support program for defenders: we preserve jobs and pay the average salary to mobilized people. We have a support program for veterans, and the Bank’s veteran community is developing. We are working to raise awareness among managers and teams on the issues of veterans’ return to civilian life. Raiffeisen Bank is recognized as one of the best employers for veterans (Forbes)

Why Raiffeisen Bank?

• Our main value is people, and we support and recognize them, educate them and involve them in changes. Join Raif’s team because for us YOU matter!
• One of the largest lenders to the economy and agricultural business among private banks
• Recognized as the best employer by EY, Forbes, Randstad, Franklin Covey, and Delo.UA
• The largest humanitarian aid donor among banks (Ukrainian Red Cross, UNITED24, Superhumans, СМІЛИВІ)
• One of the largest IT product teams among the country’s banks. • One of the largest taxpayers in Ukraine; 6.6 billion UAH were paid in taxes in 2023.

Opportunities for Everyone:

• Raif is guided by principles that focus on people and their development, with 5,500 employees and more than 2.7 million customers at the center of attention
• We support the principles of diversity, equality and inclusiveness
• We are open to hiring veterans and people with disabilities and are ready to adapt the work environment to your special needs
• We cooperate with students and older people, creating conditions for growth at any career stage

You matter at Raif!

Start: ASAP
Long-term project
Candidate location: EU !!!
Location: Berlin (Hybrid) or fully remote
Department: Technology / Digital Transformation

You'll own the infrastructure, automation, and delivery pipelines that power our internal platforms and integrations — working across cloud (Azure/GCP), containerized workloads, and enterprise systems (SAP, NestJS-based services, and internal tooling). This is a senior, hands-on role with real architectural ownership: you'll shape how we build, secure, and scale our platform, not just maintain what already exists.

What You'll Do
• Own CI/CD and delivery pipelines end-to-end — design, harden, and continuously improve pipelines with built-in security gates (SAST/DAST, dependency and container scanning, IaC compliance checks) rather than bolting security on after the fact.
• Build and evolve infrastructure as code (Terraform, and/or Pulumi) across cloud environments, treating Git as the single source of truth (GitOps) with full auditability and rollback.
• Design and operate Kubernetes-based container platforms — clusters, Helm charts, and where relevant, service mesh (Istio/Linkerd) for multi-service, multi-cluster environments.
• Drive platform engineering initiatives — build internal developer platforms / self-service tooling that reduce cognitive load for application teams (standardized environments, templated deployments, golden paths).
• Own the technical pipeline for the Secure Software Development Lifecycle (SSDLC), including security gates at each stage of build and release.
• Drive vulnerability mitigation — triage findings from scanning tools and coordinate timely remediation across teams.
• Own patch management — track, prioritize, and apply patches across infrastructure and dependencies on a defined cadence.
• Bring AI into operations (AIOps) — apply anomaly detection, intelligent alerting, and automation to reduce noise and enable self-healing pipelines and infrastructure; use AI-assisted engineering tools (e.g., Cursor, Claude Code) daily as a core part of how you build and ship.
• Own observability — instrument systems for metrics, logs, and traces; build dashboards and alerting that reflect real business and system risk, not just infrastructure noise.
• Take responsibility for cost (FinOps) — monitor cloud spend, rightsize resources, and build budget guardrails across environments.
• Support MLOps/AI infrastructure needs as our AI tooling and agentic workflows scale — model/version registries, secure API access patterns (e.g., workload identity federation), and sandboxing for autonomous agents.
• Act as a technical bridge between development, security, operations, and business stakeholders — explain trade-offs clearly, coordinate incidents calmly, and contribute to architecture discussions, not just implementation.

What You Bring
Core technical foundation!!!
• 5+ years in DevOps/SRE/Platform Engineering roles, with at least 2 years operating at a senior/lead level (system design, mentoring, on-call ownership). Strong hands-on DevSecOps experience, including SAST, DAST, SCA, container image scanning, secrets management, vulnerability remediation, security policy enforcement, and Secure Software Development Lifecycle (SSDLC).
• Deep hands-on experience with at least one major cloud provider (Azure or GCP strongly preferred given our stack; AWS a plus), including IAM, networking, and workload identity patterns. Strong understanding of networking fundamentals, including TCP/IP, HTTP/HTTPS, TLS, UDP, DNS, load balancing, ingress, and cloud networking architectures.
• Strong command of containerization and orchestration: Docker, Kubernetes in production, Helm.Strong Linux administration skills, including file permissions, ownership, process management, networking tools, shell scripting, and troubleshooting production systems.
• Proven experience with Infrastructure as Code (Terraform preferred) and GitOps workflows (ArgoCD, Flux, or equivalent).
• Solid scripting/automation skills (Python, Bash, or Go) and comfort reading/writing CI/CD pipeline configs (GitHub Actions, GitLab CI, Jenkins, or Azure DevOps).
• Required: daily hands-on experience with AI-assisted coding tools (Cursor, Claude Code, GitHub Copilot, or similar) as part of your development and infrastructure workflow — this is a must-have, not a nice-to-have. Experience with modern AI platforms or services such as Amazon Bedrock, Azure AI Foundry, Vertex AI, OpenSRE, HolmesGPT, LangChain, MCP, or similar is highly desirable.
Security & compliance
• Practical DevSecOps experience: vulnerability scanning (Snyk, OWASP Dependency-Check or similar), secrets management, and policy-as-code/compliance tooling.
• Understanding of zero-trust network design and enterprise IAM governance (relevant to regulated, multi-entity organizations).
Emerging / 2026-relevant skills
• Familiarity with AIOps concepts and tools — using AI/ML signals for incident detection, capacity planning, or pipeline self-healing.
• Working knowledge of platform engineering principles and building internal developer platforms (IDPs).
• Exposure to MLOps or AI infrastructure (GPU scheduling, model registries, agent sandboxing/network isolation) is a strong plus given our growing AI governance and agentic tooling initiatives.
• Comfort operating in a FinOps mindset — cost visibility and optimization as a shared responsibility, not a separate team's job.
Soft skills (non-negotiable at senior level)
• Strong written and verbal communication — able to explain technical trade-offs to both engineers and non-technical stakeholders.
• Calm, structured incident coordination under pressure.
• A systems-thinking mindset: understanding failure modes and designing for resilience rather than reacting to outages.
• Collaborative, low-ego approach to working across dev, security, QA, and business teams.

Nice to have
• Experience in real estate, financial services, or another regulated, multi-entity enterprise environment.
• Familiarity with SAP-adjacent integration landscapes or large-scale enterprise system migrations.
• Cloud certifications (Azure DevOps Engineer Expert, Google Professional Cloud DevOps Engineer, or equivalent).

 

DevSecOps Engineer (Senior)

Location: Remote
 

About the Role

We are looking for a highly skilled and strategic Senior DevSecOps Engineer to lead our security operations and infrastructure automation initiatives. In this role, you will bridge the gap between development, security, and operations, ensuring our on-premise environment remains secure, resilient, and efficient.

You will act as a subject matter expert, leveraging cutting-edge tools like CrowdStrike to automate threat detection and response, while maintaining robust perimeter security via Cloudflare.

Key Responsibilities

• Implementation and automation of security tools in the CI/CD process (SAST, DAST, SCA).
• Analysis of vulnerabilities in code, infrastructure and containers.
• Development and configuration of security monitoring systems, incident response.
• Monitoring and improving the security level of on-prem infrastructures.
• Interaction with developers, DevOps and security teams to implement secure practices.
• Active participation in the processes of IAM configuration, management of certificates, secrets and access policies.
• Conducting internal security audits, participation in external (e.g. penetration) tests.

Requirements

Must-have:

• Experience: 5+ years of experience in DevSecOps, Security Engineering, or a related field, with at least 2 years in a Senior role.
• Tooling Expertise: Deep hands-on experience with the following specific tools:
• Baremetal/on-premise infrastructure
• Docker (Docker Swarm is a strong plus)
• Gitlab CI 
• CrowdStrike
• Cloudflare
• ELK.
• SIEM Proficiency: Proven experience deploying and tuning SIEM solutions (e.g., Splunk, Elastic Security, Datadog, or similar).
• Infrastructure: Strong background in managing on-premise infrastructure (physical servers, data centers, virtualization, networking).
• Scripting: Proficiency in Python, Go, or Bash for automation and tooling.
   

Nice-to-have:

• Experience with Kubernetes and such tools as Wiz.io and Torq.
• Previous involvement in high-load, regulated, or 24/7 production environments (e.g., iGaming, FinTech, telecom or similar).

We offer

• Fully remote work opportunity
• Enhanced leave benefits:
• 20 days of paid vacation
• 5 paid days off
• 14 paid sick leaves
• Company clubs & communities
• Celebration gifts for personal milestones
• Corporate online events, raffles & challenges
• Corporate English program
• Corporate yoga classes
• Team-building activities
• Coworking compensation
• Training and development programs (internal & external).

We are looking for a Senior Data Engineer to design and build scalable data platforms that process large volumes of data for analytics, reporting, and business-critical applications.

You will work with distributed data processing systems, cloud infrastructure, streaming platforms, and modern data pipelines. We are looking for an engineer who can independently own production solutions and solve complex performance and architecture challenges.

Mandatory Skills

Programming & Data Processing

• Strong Python development skills
• Advanced SQL (complex queries, optimization, execution plans)
• Strong commercial experience with Apache Spark / PySpark
• Experience optimizing Spark jobs (partitioning, shuffle, joins, skew handling)

Data Engineering

• Experience building production-grade ETL / ELT pipelines
• Strong experience with Apache Airflow
• Strong hands-on experience with Apache Kafka
• Understanding of batch and streaming data processing architectures

Infrastructure & Storage

• Experience with relational databases (PostgreSQL, MySQL or similar)
• Data modeling and query optimization
• Hands-on experience with at least one cloud platform (AWS, Azure or GCP)
• Experience working with Docker, Linux, Git, and basic CI/CD pipelines

Desired Skills

• Databricks, Snowflake or similar cloud data platforms
• Kubernetes
• CDC pipelines (Debezium or similar)
• Modern analytical/storage systems (ClickHouse, Trino, Iceberg, Delta Lake)
• Monitoring tools (Grafana, Prometheus)

Responsibilities

• Build scalable batch and streaming data pipelines
• Develop and optimize Spark/PySpark data processing jobs
• Build Kafka-based ingestion and event-driven pipelines
• Design and maintain Airflow orchestration workflows
• Optimize SQL queries and improve pipeline performance
• Investigate production issues and improve system reliability
• Participate in architecture and technical design discussions

Senior-Level Expectations

• Independently design scalable data pipelines
• Debug and optimize distributed production systems
• Solve performance bottlenecks in Spark and SQL workloads
• Make technical decisions with minimal supervision
• Take ownership of production solutions end-to-end

Soft Skills

• Strong problem-solving skills
• Ownership and accountability
• Ability to work independently
• Good communication and collaboration skills
• Proactive engineering mindset

The CHI Software team is not standing still. We love our job and give it one hundred percent of us! Every new project is a challenge that we face successfully. The only thing that can stop us is… Wait, it’s nothing! The number of projects is growing, and with them, our team too. And now we need a Middle/Senior Data Engineer.
 

Requirements:

• 4+ years of experience as a Data Engineer;
• Completed Data Engineering Professional certification;
• Minimum 2 projects delivered with hands-on experience in development on Databricks;
• Experience in Apache Spark Programming with Databricks;
• Experience with Azure cloud;
• Upper-Intermediate English level.

We are looking for a Senior Data Engineer Consultant to join an AI consulting engagement focused on LLM architecture, RAG, data strategy, and AI platform advisory.
 

This is an advisory role rather than a full-time implementation position. The consultant will work with AI architects, ML engineers, MLOps specialists, and the client’s engineering team to assess the current data landscape, review proposed solutions, and provide practical technical recommendations.
 

Responsibilities
 

Data Strategy
 

• Review the existing enterprise data landscape and available data sources.
   
• Assess data readiness for foundation model training, fine-tuning, evaluation, and RAG.
   
• Recommend data acquisition, prioritization, and preparation approaches.
   
• Advise on multilingual data preparation strategies.
   

Data Pipelines
 

• Review the current ETL/ELT architecture and data processing workflows.
   
• Recommend pipeline designs for model training, inference, and evaluation.
   
• Evaluate orchestration, dataset versioning, and data traceability approaches.
   
• Assess pipeline scalability, reliability, maintainability, and performance.
   

RAG Data Engineering
 

• Review document ingestion architecture for enterprise knowledge bases.
   
• Recommend parsing, chunking, metadata enrichment, embedding, and indexing approaches.
   
• Evaluate vector database and search integration strategies.
   
• Advise on incremental updates, synchronization, access-aware retrieval, and retrieval optimization.
   

Data Governance and Quality
 

• Review data lifecycle management and data governance practices.
   
• Assess PII handling, data masking, retention policies, access control, lineage, and auditability.
   
• Recommend data validation and quality-control frameworks.
   
• Review training and evaluation datasets.
   
• Advise on monitoring data freshness, consistency, completeness, and data drift.
   

Documentation and Consulting
 

• Prepare technical recommendations, architecture assessments, and implementation guidelines.
   
• Review technical documentation, diagrams, and proposed designs.
   
• Participate in architecture reviews, design discussions, and technical workshops.
   
• Conduct knowledge-transfer sessions with the client’s engineering team.
   

Technology Stack
 

Python, SQL, Apache Airflow, Apache Kafka, Hadoop, Apache Superset, n8n, ETL/ELT, RAG Pipelines, Vector Databases, Data Governance, Cloud (AWS, Azure or GCP).
 

Preferred Domain Experience
 

Experience in banking, fintech, financial services, or another highly regulated domain is highly desirable.
 

The ideal candidate should understand domain-specific requirements related to:
 

• sensitive and confidential data;
   
• PII protection and data masking;
   
• role-based access control;
   
• data retention and auditability;
   
• regulatory and compliance requirements;
   
• secure use of enterprise data in AI and LLM solutions.
   

Engagement Details
 

• Engagement model: Part-time consulting.
   
• Workload: Flexible and non-uniform, depending on the current project phase.
   
• Expected activities: Architecture reviews, workshops, document reviews, technical assessments, and advisory sessions.
   
• Duration: Approximately 6 months.
   
• Project type: AI/LLM consulting engagement.
   
• Client interaction: Direct collaboration with the client’s engineering and architecture teams.
   
• Availability: The consultant should be able to join scheduled sessions and provide asynchronous reviews between meetings.
   

FutureMedia is a dynamic, remote-first digital services company specializing in SaaS products, AI-powered solutions, and web and mobile application development. Our team brings together diverse digital experts who focus on innovation, problem-solving, and delivering impactful, technology-driven products for clients across global markets.

We design, develop, build, and analyze. We deliver impactful digital products and services — SaaS products, AI-powered solutions, web and mobile applications. As pioneers in the digital services space, we’re a team that knows how to innovate while having fun. Remote-first, but connection and collaboration are at our core.

About the Role

Our data is a strategic asset, and we are now building the infrastructure needed to unlock it. As an early member of our Data team, reporting to the Head of Data, you will design and own the pipelines, warehouse, and tooling that turn product signals into business intelligence.
You are joining at the ground floor: the data layer is being built now, so your decisions will shape it. We treat data as a product and hold a high bar for quality and reliability. The stack includes Python, SQL, dbt, Airflow or Prefect, Snowflake or BigQuery, Segment, Amplitude, AWS or GCP, Terraform, Looker or Metabase, Fivetran or Airbyte, GitHub Actions, and Kafka (planned).

What You’ll DoPipelines & Warehouse

• Design, build, and maintain scalable ELT/ETL pipelines ingesting data from product surfaces, payment providers, and third-party APIs
• Architect and manage our cloud data warehouse (Snowflake, BigQuery, or Redshift) from the ground up
• Implement orchestration workflows (Airflow, Prefect, or similar) for reliability and full observability

• Optimise warehouse performance and cost through query tuning, clustering, and sensible warehouse sizing

   

Transformation, Quality & Governance

• Develop clean, well-documented, testable transformation layers (dbt or equivalent), applying dimensional modelling principles
• Build and govern a canonical semantic layer so metric and entity definitions stay consistent across every BI tool and consumer
• Define and enforce data quality standards, SLAs, tests, and monitoring across critical datasets, and maintain a central data catalogue with clear lineage

• Build security and governance into the platform: RBAC, PII classification and masking, encryption, and retention and deletion workflows that support privacy requests

   

Product & Engineering Partnership

• Partner with Product and Growth to instrument event tracking (Segment, Amplitude, or similar) and deliver datasets that power funnels, subscription metrics (MRR, churn, LTV), and A/B test reporting
• Collaborate with Software Engineers on data contract design, API logging, and Change Data Capture where needed

• Champion DataOps practices: version control, CI/CD for data, and documentation-as-code

   

What We’re Looking For (Must-Have)

• 3+ years of professional experience as a Data Engineer or in a closely related role
• Strong command of SQL and at least one of Python or Scala for data processing
• Hands-on experience with a modern cloud data warehouse (Snowflake, BigQuery, or Redshift)
• Experience with workflow orchestration tools (Airflow, Prefect, Dagster, or equivalent)
• Prior experience at a B2C SaaS, subscription, or marketplace business, with a grasp of funnels, churn, and LTV
• Solid understanding of data modelling principles and experience with dbt or a similar transformation framework
• Proven ability to design and scale batch and/or streaming data pipelines in production
• A strong sense of data ownership — you treat data as a product and hold a high bar for quality and reliability
• A clear communicator who can translate technical decisions into business value for non-technical stakeholders

• Comfortable handling personal data responsibly, applying access controls and privacy-aware practices

   

Nice to Have

• Familiarity with product analytics tools such as Segment, Amplitude, or Mixpanel
• Experience building or contributing to a semantic layer or canonical data model
• Experience with streaming platforms (Kafka, Kinesis) for real-time use cases
• Exposure to ML infrastructure or feature stores, a plus as we expand into AI products
• Experience setting up a data platform from scratch in a scale-up environment

Working Conditions

• Competitive compensation
• Remote-first culture with flexible working hours 
• 22 paid vacation days + local national holidays 
• Opportunity to shape the excellence across a growing engineering organisation 
• Modern stack, scalable products, and meaningful technical challenges 

We are looking for a Data Architect who will participate in the formation and development of Data Governance across the entire Bank. The main goal is to design and implement a comprehensive data architecture for the bank that ensures data quality, accessibility, security, and traceability (lineage) to support the Data Governance strategy, which ensures data consistency, business decision support, regulatory compliance, and maximization of data value as a strategic asset

Your future responsibilities:

• Designing target architecture: developing data models and requirements for their description
• Building data flow maps from source systems to reporting to ensure complete transparency of data origin
• Performing data profiling and analysis of the source system
• Formulating clear conclusions to support the end use of data
• Use metadata repositories to perform data and system integration impact analysis
• Participate in defining data exchange principles (ETL/ELT, Kafka, REST API) with a focus on data integrity
• Participate in the implementation of Data Quality Management (DQM): rules, monitoring, control
• Participate in the implementation of Data Governance controls in business processes and systems
• Identify data-related risks, develop and monitor a minimization plan
• Implement KPIs and OKRs for the Data Governance program
• Communicate results to key stakeholders

Your skills and experience:

• 3+ years of experience in banking or finance
• Expertise in data modeling techniques
• Strategic thinking and architectural approach
• Deep understanding of Data Governance Frameworks (DAMA-DMBOK, DCAM)
• Expertise in Data Quality, Master Data, Metadata, Data Security
• Strong analytical and problem-solving skills, as well as the ability to identify and solve complex data management issues
• Deep understanding of regulatory requirements (BCBS 239, GDPR)
• Communication skills: ability to translate complex data concepts into business-friendly language
• Familiarity with agile methodologies in a data environment

We offer what matters most to you:

• Competitive salary: we guarantee a stable income and annual bonuses for your personal contribution. Additionally, we have a referral program with rewards for bringing in new colleagues to Raiffeisen Bank
• Social package: official employment, 28 days of paid leave, additional paternity leave, and financial assistance for parents with newborns
• Comfortable working conditions: possibility of a hybrid work format, offices equipped with shelters and generators, modern equipment. Classification: PUBLIC
• Wellbeing program: all employees have access to medical insurance from the first working day; consultations with a psychologist, nutritionist, or lawyer; discount programs for sports and purchases; family days for children and adults; in-office massages
• Training and development: access to over 130 online training resources; corporate training programs in CX, Data, IT Security, Leadership, Agile. Corporate library • Great team: our colleagues form a community where curiosity, talent, and innovation are welcome. We support each other, learn together, and grow. You can find like-minded individuals in over 15 professional communities, reading clubs, or sports clubs
• Career opportunities: we encourage advancement within the bank across functions
• Innovations and technologies: Infrastructure: AWS, Kubernetes, Docker, GitHub, GitHub actions, ArgoCD, Prometheus, Victoria, Vault, OpenTelemetry, ElasticSearch, Crossplain, Grafana. Languages: Java (main), Python (data), Go (infra, security), Swift (IOS), Kotlin (Android). Data stores: Sql-Oracle, PgSql, MsSql, Sybase. Data management: Kafka, AirFlow, Spark, Flink
• Support program for defenders: we maintain jobs and pay average wages to mobilized individuals. For veterans, we have a support program and develop the Bank’s veterans community. We work on increasing awareness among leaders and teams about the return of veterans to civilian life. Raiffeisen Bank has been recognized as one of the best employers for veterans by Forbes

Why Raiffeisen Bank?

• Our main value is people, and we support and recognize them, educate them and involve them in changes. Join Raif’s team because for us YOU matter!
• One of the largest lenders to the economy and agricultural business among private banks
• Recognized as the best employer by EY, Forbes, Randstad, Franklin Covey, and Delo.UA
• The largest humanitarian aid donor among banks (Ukrainian Red Cross, UNITED24, Superhumans, СМІЛИВІ)
• One of the largest IT product teams among the country’s banks. • One of the largest taxpayers in Ukraine; 6.6 billion UAH were paid in taxes in 2023

Opportunities for Everyone:

• Rife is guided by principles that focus on people and their development, with 5,500 employees and more than 2.7 million customers at the center of attention
• We support the principles of diversity, equality and inclusiveness
• We are open to hiring veterans and people with disabilities and are ready to adapt the work environment to your special needs
• We cooperate with students and older people, creating conditions for growth at any career stage

Want to learn more? — Follow us on social media:

, , 

___________________________________________________________________________________________

Райффайзен Банк — найбільший український банк з іноземним капіталом. Більше 30 років ми створюємо та вибудовуємо банківську систему нашої держави.

У Райфі працює понад 5 500 співробітників, серед них одна із найбільших продуктових ІТ-команд, що налічує понад 800 фахівців. Щодня пліч-о-пліч ми працюємо, щоб більш ніж 2,7 мільйона наших клієнтів могли отримати якісне обслуговування, користуватися продуктами і сервісами банку, розвивати бізнес, адже ми #Разом_з_Україною. 

Ми шукаємо Дата Архітектора, який візьме участь у формуванні та розвитку Data Governance у масштабах всього Банку. Основна мета — проєктування та впровадження цілісної архітектури даних банку, яка забезпечує якість, доступність, безпеку та простежуваність (lineage) даних для підтримки стратегії Data Governance, яка забезпечує узгодженість даних, підтримку бізнес-рішень, відповідність регуляторним вимогам та максимізацію цінності даних як стратегічного активу.

Твої майбутні обов’язки:

• Проєктування цільової архітектури: розробка моделей даних та вимог до їхнього опису
• Побудова карт потоків даних від систем-джерел до звітності, щоб забезпечити повну прозорість походження даних
• Проводити профілювання даних та аналіз вихідної системи
• Формулювання чітких висновків для підтримки кінцевого використання даних
• Використовувати репозиторії метаданих для виконання аналізу впливу інтеграції даних та систем
• Приймати участь у визначенні принципів обміну даними (ETL/ELT, Kafka, REST API) з фокусом на цілісність даних
• Участь у впровадженні Data Quality Management (DQM): правила, моніторинг, контроль
• Приймати участь у впровадженні контролів Data Governance у бізнес-процеси та системи
• Ідентифікація ризиків, пов’язаних з даними, розробка та контроль плані мінімізації
• Впровадження KPI та OKR для Data Governance програми
• Комунікація результатів ключовим стейкхолдерам

Твій досвід та навички:

• 3+ досвід роботи в банківській або фінансовій галузі
• Експертне володіння методиками моделювання даних
• Стратегічне мислення та архітектурний підхід
• Глибоке розуміння Data Governance Frameworks (DAMA-DMBOK, DCAM)
• Експертиза в Data Quality, Master Data, Metadata, Data Security
• Сильні аналітичні навички та навички вирішення проблем, а також здатність виявляти та вирішувати складні проблеми управління даними
• Глибоке розуміння регуляторних вимог (BCBS 239, GDPR)
• Комунікаційні навички: здатність перекладати складні концепції даних на зрозумілу для бізнесу мову
• Знайомство з гнучкими методологіями в середовищі даних

Пропонуємо те, що має значення саме для тебе: 

• Конкурентна заробітна плата: гарантуємо стабільний дохід та річні бонуси за твій особистий внесок. Додатково, у нас діє реферальна програма винагороди за залучення нових колег до Райффайзен Банку.
• Соціальний пакет: офіційне працевлаштування, 28 днів оплачуваної відпустки, додатковий “декрет” для татусів, та матеріальна допомога для батьків при народженні дітей.
• Комфортні умови праці: можливість гібридного формату роботи, офіси забезпеченні укриттями та генераторами, забезпечення сучасною технікою.
• Wellbeing програма: для всіх співробітників доступні медичне страхування з першого робочого дня; консультації психолога, нутриціолога чи юриста; дисконт програми на спорт та покупки; family days для дітей та дорослих; масаж в офісі.
• Навчання та розвиток: доступ до понад 130 навчальних онлайн-ресурсів; корпоративні навчальні програми з CX, Data, IT Security, Лідерства, Agile. Корпоративна бібліотека та уроки англійської.
• Крута команда: наші колеги — це спільнота, де вітаються допитливість, талант та інновації. Ми підтримуємо один одного, вчимося разом та зростаємо. Ти можеш знайти однодумців у понад 15-ти професійних ком’юніті, читацькому чи спортивному клубах.
• Кар’єрні можливості: ми заохочуємо просування всередині банку між функціями.
• Інновації та технології. Infrastructure: AWS, Kubernetes, Docker, GitHub, GitHub actions, ArgoCD, Prometheus, Victoria, Vault, OpenTelemetry, ElasticSearch, Crossplain, Grafana. Languages: Java (main), Python (data), Go(infra,security), Swift (IOS), Kotlin (Andorid). Datastores: Sql-Oracle, PgSql, MsSql, Sybase. Data management: Kafka, AirFlow, Spark, Flink.
• Програма підтримки захисників і захисниць: ми зберігаємо робочі місця та виплачуємо середню заробітну плату мобілізованим. Для ветеранів та ветеранок у нас діє програма підтримки, розвивається ветеранська спільнота Банку. Ми працюємо над підвищенням обізнаності керівників та команд з питань повернення ветеранів до цивільного життя. Райффайзен Банк відзначений як один з найкращих роботодавців для ветеранів (Forbes).

Чому Райффайзен Банк? 

• Наша головна цінність — люди і ми даємо їм підтримку і визнання, навчаємо, залучаємо до змін. Приєднуйся до команди Райфу, адже для нас ТИ маєш значення! 
• Один із найбільших кредиторів економіки та аграрного бізнесу серед приватних банків 
• Визнаний найкращим працедавцем за версіями EY, Forbes, Randstad, Franklin Covey, Delo.UA 
• Найбільший донор гуманітарної допомогисеред банків (Червоний Хрест України, UNITED24, Superhumans, СМІЛИВІ) 
• Один із найбільших платників податків в Україні, за 2023 рік було сплачено 6,6 млрд гривень

Можливості для всіх: 

• Райф керується принципами, що фокусуються на людині та її розвитку, у центрі уваги 5 500 співробітників та понад 2,7 мільйони клієнтів  
• Підтримуємо принципи різноманіття, рівності та інклюзивності
• Ми відкриті до найму ветеранів і людей з інвалідністю та готові адаптувати робоче середовище під ваші особливі потреби
• Співпрацюємо зі студентами та людьми старшого віку, створюючи умови для зростання на будь-якому етапі кар’єри