Jobs Data Engineer

We are looking for a hands-on Senior Computer Vision Engineer to join a long-term product engineering team. The client builds hardware and software platforms for real-world outdoor mapping, inventory, and environmental analysis. This is not a standard image classification task on clean laboratory datasets. Our models process visual and sensor data captured on the go in dynamic, unpredictable outdoor environments (varying lighting, motion blur, complex natural backgrounds, changing distances). Your main focus won't be just reading R&D papers, but diagnosing where existing models fail, running experiments, and turning those experiments into robust production improvements.

Key Responsibilities:

• Analyze, improve, and optimize production CV models for object detection, segmentation, and depth analysis.
• Diagnose model errors.
• Build evaluation and experimentation pipelines for real-world, noisy data.
• Work with data captured from moving camera systems / wearables.
• Optimize inference pipelines for production integration.
   

Requirements:

• 3+ years of commercial experience in Computer Vision & ML (Python, PyTorch).
• Proven experience taking CV models into production.
• Strong expertise in Object Detection, Instance/Semantic Segmentation, or Depth Estimation.
• Solid understanding of training pipelines, dataset quality, data augmentation, and inference optimization.

• Ability to work independently on applied ML problems.

  
   

Nice to Have:

• 3D & Spatial CV: Monocular/stereo depth estimation, RGB-D, Point Clouds, Camera Geometry.

• Sensor & Navigation: SLAM, Visual-Inertial Odometry (VIO), Sensor Fusion, LiDAR.

   

• We offer:
• Flexible working schedule
• Fully remote work
• Compensation for medical, educational and sports activities
• Professional growth opportunities
• Internal knowledge-sharing talks
• Awesome team events and activities
• Paid vacation and sick leave
   

Description

We are seeking a highly skilled Сonsultant Data Engineer to be the driving force behind this massive architectural shift. You will be hands-on in moving a highly complex, highly regulated data ecosystem from an on-premise Teradata environment to a cutting-edge AWS “Lakehouse” architecture.
In this role, you will focus on building robust data pipelines, modernizing legacy code, and ensuring flawless data delivery. You will work closely with System Analysts, Automation Engineers, and Data Architects to convert hundreds of legacy scripts into modern dbt models, orchestrate them via Astronomer (Airflow), and establish governed warehousing in Databricks.

Requirements

• Cloud Platforms: Hands-on engineering experience within the AWS ecosystem (S3, IAM, Glue) and deep expertise in Databricks (SparkSQL, PySpark, governed cataloging).
• Modern Data Stack: Strong proficiency in dbt (Core or Cloud) for data transformation and understanding of modern table formats, specifically Apache Iceberg.
• Orchestration: Experience building and maintaining data pipelines using Apache Airflow (Astronomer experience is a strong plus).
• Languages: Expert-level SQL (ability to read Teradata SQL/BTEQ and write highly optimized Spark/Databricks SQL) and strong Python skills for pipeline development and Airflow DAGs.
• Legacy Systems: Familiarity with Teradata architecture and utilities (FastExport, BTEQ) to effectively understand the source systems being decommissioned.

Experience & Qualifications

• Experience: 7+ years of dedicated Data Engineering experience, with a proven track record in complex data migration projects (On-Premise to Cloud).
• Financial Services Background: Experience working in a highly regulated banking or financial services environment is strongly preferred, particularly within Risk or Finance domains.
• Engineering Best Practices: Strong grasp of CI/CD for data pipelines, Git version control, data modeling (Kimball/Inmon), and infrastructure as code (Terraform).
• Communication: Ability to work collaboratively in a fast-paced, cross-functional agile team, effectively communicating technical blockers to technical leads and project managers.

Job responsibilities

• Lakehouse Engineering: Build and maintain scalable data pipelines to migrate Consumer Risk datasets from Teradata to Amazon S3, utilizing Apache Iceberg for the lakehouse layer and Databricks for governed warehousing.
• Code Modernization (BTEQ to dbt): Perform complex code conversions, transforming up to 500 legacy Teradata BTEQ scripts into modular, version-controlled, and highly performant dbt (data build tool) models.
• Pipeline Orchestration: Design, develop, and monitor complex Directed Acyclic Graphs (DAGs) using Astronomer (Apache Airflow) to orchestrate end-to-end data workflows.
• Data Lineage & Transparency: Integrate pipelines with OpenLineage to ensure complete, end-to-end data traceability, providing the transparency required for regulatory compliance.
• Reconciliation & Parity: Work alongside the QA/Automation team to execute automated reconciliation frameworks, debugging and resolving data discrepancies to ensure strict attribute-level parity and timing equivalence during governed parallel runs

What we offer

Our goal is to build an inclusive positive culture where everyone can feel comfortable being themselves, empowering people to create their own high standards and therefore more value. We work together to promote fairness while recognising, valuing and embracing differences – providing a transparent support structure and generous training budget to help our people develop skills to progress their career. Our region supports a hybrid model that can flex across a wide spectrum of working options determined by business, customer and individual needs.

You'll benefit from a comprehensive health and wellness plan, private healthcare (clinical and mental wellbeing), discounted gym memberships, and in office yoga sessions and massages. We offer a fantastic benefits package including a competitive pension scheme and recognition schemes through bonus/reward initiatives. Colleagues are entitled to an annual volunteering day – so you can take time to support a cause close to your heart. We also love to stay social with trips to the zoo, quiz nights, sports events, theatre trips and much more.

We are an equal opportunities employer. It is our policy to promote an environment free from discrimination, harassment and victimisation, and we actively welcome applications from people with a disability or long-term health condition. As users of the Disability Confident scheme, we guarantee to interview all disabled applicants who meet the minimum essential criteria for this vacancy.

The company is a healthcare data analytics provider offering modern data infrastructure, reporting, and AI‑driven insights. Their technology focuses on improving how healthcare organizations manage, analyze, and use clinical data.

Core Solutions

•  Healthcare data platform: Consolidates structured and unstructured patient data in near real time to create a unified data foundation.

•  Longitudinal clinical data ecosystem: Enables comprehensive management and analysis of patient information.

•  Patient engagement platform: Integrates data from multiple sources to support secure communication and holistic patient care.

•  Population health management suite: Aggregates clinical and claims data, identifies at‑risk groups, and supports interventions to improve outcomes and reduce costs.

•  Care coordination and analytics tools: Provide a complete view of patient data to enhance quality, reduce costs, and support risk stratification.

•  AI and analytics services: Transform healthcare data into actionable insights for better care and operational efficiency.

Main expectations:
1.  Strong Python 3.x backend development (Flask + multithreading)
2.  Solid SQL skills and hands‑on experience with PostgreSQL
3.  Practical experience with BigQuery and Google Cloud services
4.  Containerization skills (Docker/Podman) and basic Kubernetes knowledge
5.  ETL/ELT pipeline experience and large‑scale data processing

Conditions:

• Compensation: 5500–6500 USD/month

• Contract: B2B

• Remote‑friendly

Client

Our client is a U.S.-based company specializing in services for the reverse mortgage market.

Project overview

The project focuses on advancing the capabilities and efficiency of the reverse mortgage market system through the development of new modules and features, system enhancements, and its migration to contemporary technologies.

Position overview

We are seeking an experienced UiPath Robotic Process Automation (RPA) Engineer to design, develop, implement, and support scalable enterprise automation solutions that improve operational efficiency and reduce manual effort.

The role involves collaborating with business stakeholders, Business Analysts, solution architects, and development teams to deliver secure, maintainable UiPath solutions. The engineer will contribute to the organization’s digital transformation by developing RPA solutions aligned with enterprise architecture, governance, security, and compliance standards.

Responsibilities

• Design, develop, test, deploy, and maintain UiPath automation solutions.
• Analyze business processes to identify automation opportunities and recommend optimal RPA solutions.
• Develop reusable automation components and frameworks following enterprise standards.
• Integrate UiPath solutions with web applications, desktop applications, APIs, databases, and enterprise systems.
• Build attended, unattended, and scheduled automation workflows.
• Partner with Business Analysts and business stakeholders to understand functional and technical requirements.
• Participate in process discovery workshops and automation assessments.
• Prepare solution design documents and technical specifications.
• Provide effort estimates and implementation recommendations.
• Develop automation using UiPath Studio and UiPath Orchestrator.
• Create reusable libraries, workflows, and custom activities when appropriate.
• Integrate with REST APIs, SQL databases, file systems, email platforms, and cloud services.
• Develop robust exception handling and logging mechanisms.
• Perform unit testing, system testing, integration testing, and provide support during user acceptance testing.
• Resolve automation defects and optimize existing bots.
• Ensure automation meets performance, security, and compliance standards.
• Participate in peer code reviews and technical walkthroughs.
• Deploy automation packages through UiPath Orchestrator.
• Monitor bot execution and troubleshoot production issues.
• Support scheduled automation jobs and production releases.
• Participate in production support and incident resolution.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience).
• 3–7 years of software development or RPA development experience.
• 2+ years of hands-on experience with UiPath Studio and UiPath Orchestrator.
• Strong understanding of RPA development principles and best practices.
• Experience integrating automation solutions with REST APIs, SQL databases, file systems, email platforms, and cloud services.
• Experience with exception handling, logging, testing, debugging, and production support.
• Understanding of enterprise architecture, security, governance, and compliance standards.

Company Description

Are you a Senior Data Engineer passionate about building scalable, high-performance data platforms and working with modern Lakehouse technologies? Join Sigma Software’s Data Engineering Center of Excellence and contribute to the modernization of an enterprise-scale analytics ecosystem for the retail domain.
We are looking for a Senior specialist with strong Databricks, PySpark, and cloud data engineering expertise to participate in the migration of a large-scale analytical platform from BigQuery to Databricks. You will collaborate with international teams, contribute to architectural decisions, and help shape reliable and scalable data solutions.
We at Sigma Software create opportunities for continuous learning, technology growth, and meaningful engineering impact while working on complex international projects.

CUSTOMER

Our Customer is a leading retail technology company specializing in AI-driven pricing optimization solutions for enterprise retailers. The company helps businesses improve profitability and competitiveness through advanced analytics, automation, and intelligent pricing strategies. Their platform combines business intelligence with sophisticated algorithms to support data-informed pricing decisions at scale for global retail organizations.

PROJECT

The project focuses on the strategic migration of a large-scale analytical platform from a legacy BigQuery ecosystem to a modern Databricks Lakehouse architecture. The platform processes high-volume retail datasets, machine learning workloads, analytics pipelines, and customer-specific business logic.
As part of the modernization initiative, the engineering team is implementing scalable Spark-based processing, Delta Lake architecture, medallion data layers, and modern governance practices. The role offers an opportunity to work with distributed data processing systems, optimize large-scale workloads, and contribute to the evolution of an enterprise-grade data platform.

Key Technologies: Databricks, Apache Spark, PySpark, Delta Lake, Python, SQL, Airflow, GCP, CI/CD, Unity Catalog

Job Description

• Participate in the migration of a large-scale analytical platform from BigQuery to Databricks
• Design and implement scalable Lakehouse architectures using Databricks and Delta Lake
• Analyze existing ETL / ELT workloads and define migration approaches
• Develop and optimize data pipelines processing large volumes of retail and analytical data
• Implement incremental processing strategies and scalable transformation frameworks
• Build and maintain Spark-based data processing solutions using PySpark
• Design and maintain medallion architecture layers including Bronze, Silver, and Gold
• Implement data governance and security best practices using Unity Catalog
• Collaborate with Data Science, Analytics, Product, and Customer Engineering teams
• Participate in architecture discussions and technical solution design
• Develop reusable data platform components and engineering standards
• Conduct code reviews and contribute to platform reliability and maintainability
• Troubleshoot and optimize complex SQL and Spark workloads
• Support production deployments and platform modernization activities

Qualifications

• 5+ years of professional experience as a Data Engineer
• Strong programming skills in Python and advanced SQL
• Hands-on commercial experience with Databricks
• Strong knowledge of Apache Spark, primarily PySpark
• Experience designing and building modern cloud-based data platforms
• Experience developing ETL / ELT pipelines and large-scale data processing solutions
• Hands-on experience with Delta Lake
• Experience with Spark Declarative Pipelines
• Experience with cluster monitoring, metrics analysis, and performance optimization
• Strong understanding of distributed data processing architectures
• Solid understanding of data warehousing concepts and dimensional modeling
• Experience with Airflow or similar orchestration tools
• Experience optimizing complex analytical SQL workloads
• Experience implementing CI / CD practices for data engineering platforms
• Strong troubleshooting and performance optimization skills
• Ability to work collaboratively in cross-functional international teams
• Upper-Intermediate or higher English level

WILL BE A PLUS

• Experience working with GCP cloud services
• Experience with AWS or Azure cloud platforms
• Experience in retail analytics or pricing optimization domains
• Experience supporting machine learning or AI-related data workloads
• Experience with platform modernization and cloud migration initiatives

Additional information

PERSONAL PROFILE

• Strong analytical and problem-solving mindset
• Proactive and ownership-driven approach
• Ability to work independently and collaboratively
• Good communication and stakeholder collaboration skills
• Passion for scalable data engineering and modern data platforms
• Interest in continuous learning and technology innovation

We're looking for a Middle+ Data/Databricks Engineer to join our data team and take ownership of pipelines built on Databricks. You'll design and run production-grade ETL/ELT workloads, work with the lakehouse (Delta Lake) architecture, and partner closely with analysts, data scientists, and business stakeholders who rely on the data you deliver. "Middle+" here means roughly 3–5 years of hands-on data engineering experience: you can own a pipeline end to end with minimal supervision, make sound design decisions, and are starting to mentor more junior engineers — without yet carrying full architectural ownership of the platform.

Contract & Logistics

• Contract type: B2B (valid Czech IČO / trade license required).
• Location: Remote, candidate must be based in the Czech Republic; occasional visit to Prague office.
• Start date: ASAP
• English: Fluent 
• Czech: Native/Fluent 

What You'll Do

• Design, build, and maintain scalable ETL/ELT pipelines on Databricks using PySpark and SQL.
• Implement and evolve Delta Lake tables following a medallion (bronze/silver/gold) architecture.
• Develop batch and, where needed, streaming data processing jobs (Structured Streaming).
• Build and maintain CI/CD for Databricks notebooks and jobs (Databricks Asset Bundles, Repos, Git-based workflows).
• Orchestrate pipelines with Databricks Workflows, Azure Data Factory, Airflow, or similar tools.
• Monitor job performance and cluster costs; troubleshoot failures and optimize for reliability and spend.
• Implement data quality checks, testing, and monitoring for critical datasets.
• Collaborate with analysts, data scientists, and business stakeholders to translate requirements into data models.
• Participate in code reviews, document technical decisions, and help shape engineering best practices.
• Provide guidance and informal mentorship to junior team members.

What We're Looking For

• 3+ years of hands-on experience with Apache Spark, ideally on Databricks specifically.
• Strong PySpark and SQL skills, including performance tuning of Spark jobs.
• Practical experience with Delta Lake and lakehouse architecture concepts.
• Solid grasp of data modeling (dimensional modeling, star schema) and ETL/ELT design patterns.
• Experience with at least one major cloud platform — Azure, AWS, or GCP (Azure Databricks is a plus).
• Familiarity with pipeline orchestration tools (Databricks Workflows, ADF, Airflow, or equivalent).
• Working knowledge of Git and CI/CD practices for data engineering.
• Understanding of data governance, access control, and security basics (Unity Catalog is a plus).
• Good written and spoken English; Czech or Slovak is a plus but not required.
• Comfortable working independently and communicating clearly in a remote, distributed team.

Nice to Have

• Databricks certification (Data Engineer Associate or Professional).
• Experience with streaming technologies such as Kafka or Azure Event Hubs.
• Experience with dbt for transformation and testing.
• Solid Python software-engineering practices — testing, packaging, typing.
• Infrastructure-as-code experience (Terraform).
• Exposure to MLOps or ML pipeline support.
• Experience in a regulated or large enterprise data environment.

What We Offer

• Fully remote work with flexible hours, based anywhere in the Czech Republic.
• Long-term B2B cooperation with a stable pipeline of work.
• A modern, actively evolving data stack rather than legacy maintenance work.
• Direct collaboration with senior engineers and architects — real input on design decisions.
• Budget for training, certifications, and conference attendance.
• A flat structure with fast decision-making and minimal bureaucracy.

On behalf of our client, we are looking for a Senior Ceph/Rook-Ceph + Kubernetes Storage Engineer

Requirements:

- 5+ years of experience in DevOps, SRE, infrastructure, or storage engineering

- Deep hands-on production experience with Ceph

- Strong experience with Rook-Ceph and Kubernetes storage/CSI

- Solid Kubernetes and Linux administration skills

- Experience with Ansible and Helm

- Monitoring with Prometheus and Grafana

- Strong troubleshooting skills across storage performance, latency, disk failures, networking, and recovery

- Good understanding of CRUSH topology, failure domains, replication, and storage architecture

- Good English communication skills

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

Our client is a performance rights organization in the United States. It collects blanket license fees from businesses that use music, entitling those businesses to play or sync any songs from the client’s repertoire of over 22.4 million musical works. On a regular basis, the client distributes the money to songwriters, composers, and music publishers as royalties to those members whose works have been performed.

Requirements:

• Databricks Expertise: Minimum of 3+ years of proven, previous Databricks administration experience in a complex, multi-tenant enterprise environment.
• Advanced Terraform: Strong Terraform skills. You must have hands-on experience building and maintaining reusable modules specifically utilizing the Databricks Terraform Provider.
• Strong understanding of cloud-native IaC (Infrastructure as Code) like Terraform for automating instance provisioning
• Cloud IAM Mastery: Deep, practical knowledge of Cloud Identity and Access Management (IAM), including writing secure IAM policies, managing roles, cross-account access, and secrets management.
• Robust cloud networking experience
• Scripting: Proficiency in Bash

Job responsibilities:

• Environment Ownership: Own the technical implementation of all Databricks environment configuration changes across multi-workspace environments.
• Platform Lifecycle: Manage Databricks runtimes, cluster policies, and coordinate seamless platform upgrades.
• Infrastructure as Code (IaC): Utilize strong Terraform skills to programmatically provision, update, and manage all Databricks resources (workspaces, clusters, tokens, policies) and cloud infrastructure, eliminating manual configurations.
• Cloud Security & Identity (IAM): Architect and enforce secure access models. Manage Cloud Identity and Access Management (IAM) integrations for users, groups, and service principals.
• Secure Cloud Networking: Design, implement, and maintain secure cloud networking architectures for Databricks.
• Cost Optimization: Actively review current environment setups—including cluster configurations, instance types, and data storage parameters—to identify and execute cost-optimization opportunities.
• Efficiency Strategies: Provide expert input on automation, auto-scaling, and monitoring strategies to drastically reduce ongoing compute and storage costs.

About the Opportunity

We are seeking a highly motivated Senior Data Engineer to join an enterprise technology team working on modern, AI-enabled data platforms. This role is ideal for an experienced engineer who enjoys building scalable data solutions, collaborating with cross-functional teams, and driving engineering best practices in a cloud-native environment.

You will work on enterprise-grade applications and data processing solutions using modern technologies including Azure, Databricks, Python, and microservices.

Key Responsibilities

• Define and promote engineering best practices, coding standards, and development processes.
• Conduct code reviews to maintain high-quality, maintainable software.
• Design, develop, and maintain scalable Apache Spark applications.
• Build efficient and reliable data processing and transformation pipelines.
• Write clean, well-documented, and maintainable Python code.
• Optimize applications for performance, scalability, and efficient data handling.
• Collaborate with engineering, product, and business stakeholders to deliver high-quality solutions.
• Troubleshoot and resolve technical issues to ensure system reliability.
• Create and maintain technical documentation, workflows, and development standards.
• Communicate effectively with internal teams and external stakeholders while supporting project delivery.

Required Qualifications

• 5+ years of professional software engineering or data engineering experience.
• Strong experience with Apache Spark using Databricks and/or Azure Synapse/Fabric.
• Advanced Python programming skills, including data manipulation with Pandas, Polars, or similar libraries.
• Experience working with Parquet, Delta Tables, and other columnar storage formats.
• Solid understanding of large-scale data processing, transformation, and analytics workflows.
• Experience designing scalable applications using microservices architecture.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent organizational, communication, and time management abilities.
• Ability to work independently while collaborating effectively within distributed teams.

Preferred Qualifications

• Experience with Microsoft Azure cloud services, including Data Lake, Blob Storage, Service Bus, Redis, and related services.
• Familiarity with FastAPI.
• Experience with Docker and Kubernetes.
• Exposure to modern AI technologies, RAG pipelines, or large language model (LLM) applications is a plus.

Technology Stack

• Azure Cloud
• Apache Spark / Databricks
• Python
• Azure SQL
• MongoDB
• .NET 8 / ASP.NET Core
• Microservices Architecture
• GitHub Enterprise
• Angular
• Docker & Kubernetes
• AI/LLM technologies (LangChain, LangGraph, RAG)

About This Role:

We're looking for a Senior, dbt-specialised Analytics Engineer to build and maintain the business-critical data models behind the client's credit, payments, and fraud/AML reporting. Our client is a fast-growing European fintech company in the business spend management space — corporate cards and related financial products — serving SME and mid-sized business customers across the EU and UK, in a regulated environment with GDPR compliance obligations. Engineering is organized into cross-functional squads, with platform/enabling teams providing shared tooling horizontally. The client already runs an AI-native engineering practice: Claude Code and GitHub Copilot are used daily, supported by a growing library of shared, versioned Skills embedded in key repositories, enabling an end-to-end flow from ticket to implementation, testing and PR in several codebases. AI tool/connector rollout follows an approved-list and pilot process. The client is AWS-first overall; for data platform and analytics workloads it also runs GCP, with BigQuery as the primary data warehouse. Day-to-day coordination is Slack-first, with Linear for ticket tracking, GitHub for code/PR review, and Notion as the knowledge base.

Key Responsibilities:

• Build and maintain business-critical dbt data models.
• Model data powering credit, payments, and fraud/AML reporting (working from aggregated/modeled data, not raw access to real customer/transaction data — see note above).
• Apply strong SQL and data-modelling skills.
• Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation.
• Embed directly into a client squad as a hands-on Individual Contributor (not a coaching/managerial role).

Must-Have Skills:

• Experience with dbt.
• Strong SQL and data-modelling skills.
• Experience building and maintaining business-critical data models for credit, payments, and fraud/AML reporting.
• BigQuery — the client's stated primary data warehouse for data platform and analytics workloads.
• Experience with fintech domain. 

Nice-to-Have Skills:

• Git — standard, expected tooling, but not explicitly named in the RFP for this role.

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!

Location: Warsaw, Poland
Format: On-site
Seniority level: Middle

At EPC Network, we're not just a digital marketing company, we're a platform for career transformation and personal growth. Our people-first approach shapes our corporate culture, fostering a team of passionate, smart, and energetic individuals who strive to grow professionally in an international, fast-paced environment.
As a Middle Data Engineer, you'll own the pipelines, integrations, and data models within your assigned business domain — making sure the data our teams rely on is accurate, fresh, and well documented. You will work closely with the Analytics team (Data Analyst and Unit Manager) and cross-functional stakeholders, and report to the Unit Manager.

Key Responsibilities:

• Develop and maintain ETL/ELT pipelines within your domain, following the team's established patterns and standards
• Work with data from APIs, third-party platforms, and internal sources; maintain existing API integrations (pagination, authentication, retries, rate limits)
• Write idempotent pipelines that are safe for reruns and backfills, and adapt them to changes in source data schemas
• Implement and maintain data quality checks — freshness, completeness, uniqueness, nulls, accepted values
• Detect and resolve issues (duplicates, gaps, delays) in your area, investigate root causes, and escalate complex or cross-domain cases to Senior/Lead
• Build and maintain fact tables, dimension tables, and analytical marts, applying agreed naming conventions, table structures, and documentation standards
• Clarify dataset requirements with other teams and document your work — datasets, transformation logic, known limitations
   

Requirements:

• 2–3+ years as a Data Engineer, Analytics Engineer, BI Engineer, or in a similar role
• Solid SQL: window functions, joins, deduplication, experience with large datasets
• Hands-on experience with a cloud data warehouse (BigQuery is a strong plus)
• Experience building or maintaining ETL/ELT pipelines — working within an existing architecture also counts
• Working proficiency in Python for data processing, simple API integrations, logging, and error handling
• Basic experience with dbt (or a similar SQL transformation framework), or readiness to ramp up quickly
• User-level familiarity with an orchestration tool (Airflow / Prefect / Dagster) — you don't need to architect one
• Understanding of pipeline monitoring, data quality checks, and basic secure data access principles (service accounts, secrets)
• Clean, maintainable code and the habit of documenting your work
• Ability to independently drive assigned tasks and escalate architectural questions when needed
• English B2 or higher
   

Nice to have:

• Experience with marketing platforms, CRM, tracking, or attribution systems
• Familiarity with BI tools (Looker Studio, Tableau, Power BI)
• Experience with high-volume event-level data
• Experience with Git
• Familiarity with GCP services such as Cloud Composer and Cloud Storage
   

What it means to be part of our Team:

• Multinational and intercultural experience
• Corporate library
• Growth opportunities, cutting-edge frameworks and technologies
• Plenty of engaging team-building and social events
• Bonuses according to the policy
• 21 paid vacation days & 14 paid sick leaves
• Cozy office in Warsaw, Kyiv available for you whenever you need it
• Coffee, tea, Red Bull, sweets, fruits, and more snacks
   

💌 Interested?
We're always on the lookout for passionate, driven, and curious people to join our team. If that sounds like you — we'd love to hear from you!

Join Zutobi - a fast-growing global edtech company revolutionizing driver education!
At Zutobi, we're on a mission to empower people through digital learning. Our flagship product, Zutobi Drivers Ed, helps millions of learners prepare for their driver's license exams through engaging and innovative learning experiences.
 

Our team is growing, and we're looking for a DevOps Engineer to join our existing DevOps team and help us scale our infrastructure, improve automation, and keep our services reliable as we grow. 

We use Kubernetes (GKE) as our primary platform, so hands-on experience is a plus - but if you're strong on the fundamentals and eager to learn, we'll get you up to speed.
 

What you'll do:

• Build, optimize, and maintain CI/CD pipelines to streamline development and deployment.
• Monitor and improve system reliability, scalability, and security.
• Automate cloud infrastructure management and configuration.
• Collaborate with developers to design and implement infrastructure best practices.
• Troubleshoot and resolve infrastructure-related issues, owning problems end to end.
• Ensure high availability and performance of our production environments.

What we're looking for:

• 2+ years of experience in DevOps (or 3+ years in SysAdmin) - comfortable owning tasks independently, not just executing tickets.
• Strong Linux skills: scripting (bash), monitoring (Prometheus, Grafana, Zabbix), log analysis, database management, backup and restore.
• Solid hands-on experience with Docker.
• Understanding of security best practices and infrastructure automation.
• English level: B2+ (we work in an international environment).

Nice-to-have: 

• Experience with Google Cloud / GKE (our primary platform), or AWS.
• Kubernetes, Terraform, Helm.
• CI tooling: GitLab CI, GitHub Actions.

💙 What we offer

• Culture: Empowering, ’Bottom Up’ culture valuing initiative, collaboration, and continuous learning, aligned with values of Safety, Simplicity, Modernity, Encouragement, Helpfulness, and Accountability.
• Impact & Growth: Work with an industry-leading product (250,000+ monthly users, 10M+ downloads).
• Innovation: Freedom to innovate and utilize expertise in a company that encourages ideas and initiative.
• Work Flexibility: Remote work with flexible 40-hour/week schedule, accommodating team meetings and collaboration.
• Vacation: 20 business days (4 weeks) annual leave.
• Sick Leave: 20 business days (4 weeks) annual sick leave.
• Holidays: Ukrainian public holidays are default days off.
• Learning & Development: Reimbursement for development courses/training, fostering a continuous professional development culture where employees seek opportunities and managers coach teams.

About AppsFlyer:

AppsFlyer provides a SaaS marketing analytics platform that measures and optimizes marketing activities across mobile, web, CTV, PC, and console applications. AppsFlyer is known for its massive backend production. At any given moment, thousands of servers are consuming 150+ billion mobile app events, crunching our users’ data, serving requests, and communicating on a massive scale.

To maintain the universe we call AppsFlyer, we practice modern production operations with a complete self-serve CI/CD platform, a highly integrated observability stack for our microservices, backends, and infrastructure, and a culture of ownership and eagerness for quality.

The Analytics group is responsible for showing our clients the stories their data is telling. Through complex aggregation, mission-tailored analytical databases, and carefully crafted APIs, we are able to provide slice-and-dice analysis in our beautiful dashboards and through the use of external integrations.

About the Role:

As a Data-Oriented Backend Engineer within the Analytics group at AppsFlyer, you will own the end-to-end journey of event data — from ingestion and processing to storage, modeling, and API delivery.

You will design and implement end-to-end features — from streaming and batch data processing to database modeling and API development, design and implement data pipelines using, choose and optimize analytical databases, and integrate new components in our hybrid microservices environment while collaborating closely with product managers and cross-functional engineering teams. You will tackle challenges around real-time data delivery, high-throughput processing, and production reliability, contributing to our CI/CD infrastructure and observability tooling. This role offers autonomy to influence architecture, mentor peers, and extend our open-source or community presence through talks and publications.

Key Responsibilities:

• Implement end-to-end backend and data infrastructure features, including streaming and batch pipelines, storage selection, and schema modeling.
• Collaborate with product managers and cross-functional teams to define, prioritize, and deliver complex analytics services.
• Design and optimize high-throughput, low-latency distributed systems to meet performance and scalability targets.
• Develop and maintain microservices-based APIs that serve real-time customer requests.
• Build and operate data ingestion and processing workflows using modern orchestration frameworks.
• Perform root cause analysis on production incidents, drive resolutions, and participate in on-call rotations.
• Enhance self-serve CI/CD pipelines and improve observability tooling to increase delivery velocity and system reliability.

• Share expertise through internal or external talks, blog posts, and contributions to open-source projects.

   

  Required Competence and Skills:

• Minimum 3 years of software development experience, with a focus on backend engineering with any of the programming languages(C#, Go, Scala, Java)
• Experience building backend services, APIs and distributed systems.
• Experience working with large-scale production databases in high-load environments(e.g. ClickHouse, BigQuery, Redshift, Druid, MongoDB, Elasticsearch, DynamoDB)
• Experience designing or maintaining data pipelines or production data workflows.
• Ability to solve production issues involving performance, scalability or data quality.
• Understanding of different data processing architectures (batch, streaming, etc.) and their trade-offs.
• Experience working with public cloud platforms (e.g., AWS, GCP, Azure).
• Strong English communication skills.
• B.Sc. in Computer Science or equivalent.
  
  Nice to Have:
• Experience with workflow orchestration frameworks such as Airflow.
• Familiarity with large-scale production ETL pipelines.
  Prior work with production Go backend services; knowledge of Clojure is a plus.
• Exposure to BigQuery at production scale.
• An “AI mindset”: familiarity with developer productivity tools like GitHub Copilot or Cursor.

Why Us:

• We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).
• We provide full accounting and legal support in all countries we operate.
• We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.
• We offer a highly competitive package with yearly performance and compensation reviews.
  
  The location is Kyiv only.

At TechBiz Global, we provide recruitment services to top clients across our portfolio. We are currently looking for an experienced AVEVA Developer to join one of our clients’ teams. If you are seeking an exciting opportunity to grow in an innovative industrial environment, this could be the perfect fit for you.
 

Responsibilities

•Development, configuration, and maintenance of applications based on the AVEVA System

Platform (InTouch, Application Server, Historian)

• Creation and further development of HMI visualizations, scripts, and templates

• Integration and configuration of I/O servers, communication drivers (e.g., OPC UA/DA), and

interfaces to higher-level systems (MES/ERP)

• Fault analysis, troubleshooting, and system optimization during ongoing production operation

• Performing software updates, migrations, and system backups

• Documentation of system changes in accordance with internal quality standards

• Close collaboration with Production, Maintenance, and IT

• Support during the commissioning of new plant components

• Taking on Second Level Support for complex faults and escalations

Job requirements

• Experience with AVEVA System Platform / Wonderware
• Knowledge of InTouch and Application Server
• Experience with SQL and VBScript
• Understanding of industrial communication protocols
• PLC programming knowledge is an advantage
• Slovak and English are mandatory
• German is an advantage
• Willingness to work early and late shifts

• Willingness to participate in on-call duty

   

What We Offer

• Competitive salary
• Shift and on-call allowances
• Professional development opportunities
• AVEVA certification support
• Structured onboarding