Jobs Data Engineer

As a Data Engineer, you’ll play a key role in building modern, scalable, and high-performance data solutions on Google Cloud Platform (GCP). You’ll be part of our growing Data & AI team, designing and implementing data architectures that help clients unlock the full potential of their data.

Your job’s key responsibilities are:

• Building efficient and scalable ETL/ELT processes to ingest, transform, and load data from various structured and unstructured sources (databases, APIs, streaming platforms) into BigQuery and Cloud Storage
• Implementing data ingestion and real-time processing using Dataflow (Apache Beam) and Pub/Sub for batch and streaming workflows
• Developing SQL transformation workflows with Dataform, including version control, testing, and automated scheduling with built-in quality assertions
• Creating efficient, cost-optimized BigQuery queries with proper partitioning, clustering, and denormalization strategies
• Orchestrating complex workflows using Cloud Composer (Apache Airflow) and Cloud Functions for event-driven data processing
• Implementing centralized data governance and metadata management using Dataplex with automated cataloging and lineage tracking
• Monitoring and optimizing data pipelines for performance, scalability, and cost using Cloud Monitoring and Cloud Logging
• Collaborating with data scientists and analysts to understand data requirements and deliver actionable insights
• Staying up to date with GCP advancements in data services, BigQuery features, and data engineering best practices

Essential Skills:

• 3+ years of hands-on experience as a Data Engineer with proven expertise in Google Cloud Platform (GCP)
• Strong experience with BigQuery (SQL, partitioning, clustering, optimization) and Dataflow (Apache Beam)
• Strong programming skills in Python with experience in data manipulation libraries (PySpark, pandas)
• Expert-level SQL proficiency for complex transformations, optimization, and analysis
• Proficiency with Dataform for modular SQL-based data transformations and data pipeline management
• Solid understanding of data warehousing principles, ETL/ELT processes, dimensional modeling, and data governance
• Experience integrating data from various APIs and streaming systems (Pub/Sub)
• Cloud Composer experience for workflow orchestration
• Excellent communication and collaboration skills in English (min. B2 level)
• Ability to work independently and as part of an agile team

Beneficial Skills:

• Google Professional Data Engineer certification
• Knowledge of BigLake for unified access and management of structured and unstructured data
• Experience with Dataplex for managing metadata, lineage, and data governance
• Familiarity with Infrastructure-as-Code (Terraform) for automating GCP resource provisioning and CI/CD pipelines
• Experience with data visualization tools such as Looker, Looker Studio, or Power BI
• Interest in or experience with machine learning workflows using Vertex AI or similar platforms

Join Whitechain — Build the Future of Web3!

At Whitechain, we’re on a mission to revolutionize blockchain, smart contracts, and cryptography. As part of the WhiteBIT ecosystem, we’re building cutting-edge Web3 solutions, from our own EVM blockchain to non-custodial wallets, DeFi platforms, and GameFi experiences.We’re looking for ambitious innovators to help us bridge the gap between retail and corporate blockchain adoption. If you’re passionate about decentralization, Web3, and shaping the future of digital economies, this is your chance to make an impact!

The future of Web3 starts with you — join us as a DevOps Engineer!
 

Requirements:

— 3+ years in DevOps / SRE / infrastructure roles
— 1 year experience with blockchain/ crypto infrastructure background (Ethereum, OP Stack or similar)
— Strong Kubernetes: deployment, debugging, network policies, Helm
— Terraform (modules, state management, multiple providers)
— CI/CD with GitHub Actions or equivalent; GitOps principles
— AWS (IAM, VPC, EC2, S3, KMS)
— Confident Linux administration and Bash scripting
— Monitoring and alerting with Prometheus / Grafana
— Git and PR-based workflow

Would be a plus:

— Direct OP Stack experience (op-node, op-reth, batcher, proposer, conductor)
— ArgoCD and GitOps in production
— Ansible
— Cloudflare (WAF, rate limiting, CDN)
— Key management: AWS KMS or HashiCorp Vault
— Incident response experience and postmortem writing
 
 

Responsibilities:

— Operate and evolve Kubernetes clusters (testnet and upcoming mainnet) via ArgoCD and Helm
— Deploy, upgrade and troubleshoot OP Stack components: op-node, op-reth, batcher, proposer, conductor
— Maintain infrastructure as code: Terraform (AWS, Cloudflare) and Ansible for node configuration
— Own and improve CI/CD pipelines (GitHub Actions): image builds, registry publishing, automated IaC tag bumps
— Maintain monitoring and alerting (Prometheus, Grafana); respond to alerts for sequencer lag, batcher stuck, L1 sync, disk
— Participate in the on-call rotation after onboarding
— Follow and keep runbooks up to date; document on-chain and operational procedures
— Configure and protect public RPC endpoints (rate limiting, Cloudflare WAF)

Work conditions:

Immerse yourself in Crypto & Web3:

— Shape the Future — Work on high-impact blockchain products at the forefront of Web3.
— Innovate & Create — Your ideas drive real-world solutions and technological breakthroughs.
— Global Reach — Build scalable solutions for businesses and users worldwide.
— Web3-Powered Culture — A team of visionaries who believe in decentralization and innovation.
Work-Life Balance & Well-being:
— Modern equipment.
— Comfortable working conditions, and an inspiring environment to help you thrive.
— 24 calendar days of paid leave.
— Additional days off for national holidays.

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.

Join an exciting journey to create a cutting-edge Consumer Data Lake for a leading global organization based in Europe. This platform will unify, process, and leverage consumer data from various systems, unlocking advanced analytics, insights, and personalization opportunities. As a Senior Data Engineer, you will play a pivotal role in shaping and implementing the platform's architecture, focusing on hands-on technical execution and collaboration with cross-functional teams.

Your work will transform consumer data into actionable insights and personalization on a global scale. Using advanced tools to tackle complex challenges, you’ll innovate within a collaborative environment alongside skilled architects, engineers, and leaders.

Key Responsibilities:

• Hands-On Development: Build, maintain, and optimize data pipelines for ingestion, transformation, and activation.
• Create and implement scalable solutions to handle diverse data sources and high volumes of information
• Data Modeling & Warehousing: Design and maintain efficient data models and schemas for a cloud-based data platform.
• Develop pipelines to ensure data accuracy, integrity, and accessibility for downstream analytics.
• Collaboration: Partner with Solution Architects to translate high-level designs into detailed implementation plans.
• Work closely with Technical Product Owners to align data solutions with business needs.
• Collaborate with global teams to integrate data from diverse platforms, ensuring scalability, security, and accuracy.
• Platform Development: Enable data readiness for advanced analytics, reporting, and segmentation.
• Implement robust frameworks to monitor data quality, accuracy, and performance.
• Testing & Quality Assurance: Implement robust security measures to protect sensitive consumer data at every stage of the pipeline
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA ..) and internal policies.
• Monitor and address potential vulnerabilities, ensuring the platform adheres to security best practices.

Requirements:

• Over 4+ years of experience showcasing technical expertise and critical thinking in data engineering.
• Hands-on experience with DBT and strong Python programming skills.
• Proficiency in Snowflake and expertise in data modeling are essential.
• Demonstrated experience in building consumer data lakes and developing consumer analytics capabilities is required.
• In-depth understanding of privacy and security engineering within Snowflake, including concepts like RBAC, dynamic/tag-based data masking, row-level security/access policies, and secure views.
• Ability to design, implement, and promote advanced solution patterns and standards for solving complex challenges.
• Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure).
• Practical experience with Big Data batch and streaming tools.
• Competence in SQL, NoSQL, relational database design (SAP HANA experience is a bonus), and efficient methods for data retrieval and preparation at scale.
• Proven ability to collect and process raw data at scale, including scripting, web scraping, API integration, and SQL querying.
• Experience working in global environments and collaborating with virtual teams.
• A Bachelor’s or Master’s degree in Data Science, Computer Science, Economics, or a related discipline.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

PwC Cloud & Digital team supports global cloud projects across Cloud Strategy, Migrations, Data Analytics, and DevOps. We help clients adopt cloud infrastructure, modernize data platforms, and optimize operations.

Your future role:

• Building data platforms (data warehouses, lakes, lakehouses) using Azure Databricks, MS Fabric, Azure Data Factory.
• Designing data flows using medallion architecture and supporting data migrations from legacy systems.
• Conducting data assessments with Data Modelers/Analysts and addressing data quality issues.
• Working with senior stakeholders to gather requirements and support modern data architecture design.
• Supporting Data Governance activities, especially around MDM and Data Quality.
• Understanding Data Science/Analytics use cases in industries like Consumer Goods, Retail, Manufacturing, or Financial Services.

Apply if you have:

• 4+ years of experience in Data Engineering or related fields (BI, Data Science).
• Hands‑on experience with Databricks, Snowflake, BigQuery, MS Fabric.
• Experience building data warehouses/lakehouses with Azure Data Factory / Synapse.
• Skills in PySpark/Python and SQL.
• Some exposure to CI/CD (Azure DevOps, Jira).
• B2+ English and ability to prepare technical documentation.
• Experience using modern tech and AI tools in daily work.

Nice to have:

• Cloud certifications (Azure/AWS/GCP) and Data Governance certifications.
• Training via platforms like Coursera/Udemy/Datacamp.
• Knowledge of data modelling (e.g., Kimball), Data Strategy, Data Quality, and MDM.
• Experience with Agile (Scrum), ML/GenAI use cases, or Agentic AI for data automation.
• Work with senior stakeholders (e.g., CDOs) in Manufacturing, Consumer Goods, or Financial Services.
   

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

We are looking for a Trainee Big Data Engineer who is interested in starting a career in Data Engineering.

You will join an experienced data engineering team and have the opportunity to learn how data is collected, processed, transformed, and prepared for analytics. You will work with Python, SQL, and modern Big Data technologies while receiving guidance and support from experienced engineers.

Commercial experience is not required - we are happy to consider candidates with knowledge gained through university studies, courses, internships, or personal projects. This is a great opportunity to gain practical experience with real-world data and learn how modern data engineering solutions are built.

Responsibilities:

• Assist with building and maintaining data pipelines.
• Work with data from different sources.
• Help clean and transform data.
• Write basic SQL queries.
• Use Python for data processing.
• Participate in data quality checks and troubleshooting.
• Learn and work with Big Data technologies such as PySpark / Apache Spark.
• Collaborate with experienced Data Engineers and Data Analysts.
• Learn and apply best practices in data engineering.

Requirements:

• Basic knowledge of Python.
• Basic knowledge of SQL.
• Basic understanding of relational databases.
• Understanding of basic data processing and ETL/ELT concepts.
• Familiarity with data structures and algorithms.
• Basic understanding of cloud computing.
• Strong interest in Data Engineering and Big Data.
• English — Upper-Intermediate (B2) or higher.

Would Be a Plus:

• Basic knowledge of PySpark / Apache Spark.
• Familiarity with Palantir Foundry or Databricks.
• Understanding of data warehouses or data lakes.
• Basic knowledge of data modeling.
• Experience with Git.
• University degree or ongoing studies in Computer Science, Data Engineering, Mathematics, or a related field.
• Academic, personal, internship, or course projects related to Python or Data Engineering.

Senior Data Engineer
 

We’re a London-based fintech on a mission to help banks and small businesses thrive in a digital-first economy. Founded in 2017, we bring together the energy and flexibility of a high-growth scale-up with the backing of global financial institutions. Our cloud-based platform powers end-to-end merchant services for banks, combining payments and business banking into one seamless experience. We partner with trusted names like NatWest (Tyl by NatWest), NAB (NAB Hive) and Truist (Truist Merchant Engage) in the United States to help their small business customers grow and succeed.
 

We’re a close-knit team of designers, engineers, and financial services experts who care deeply about what we build and how we work together. We value curiosity, collaboration, and making things better every day. Whether you’re technical, creative, or commercial, you’ll find space here to do your best work, develop your skills, and be part of something meaningful. We’re headquartered in London and expanding our team in South Africa – and we’d love for you to be part of the journey.
 

The role
 

As a Senior Backend Engineer in Data, you will own one or more components of our backend microservice applications. You will join the team that builds and maintains the data ingestion pipelines that turn raw banking and transactional data into actionable insights.
 

This is a great opportunity to get full exposure to the entire tech stack involved in building data pipelines for ingestion, data persistence and data APIs powering our micro-frontends at scale. We have a fun environment with a high level of responsibility, autonomy, trust and transparency and work very closely with the product development and business teams.
 

Responsibilities
 

• Design and implement scalable ingestion pipelines that work in both streaming and batch modes.
 

• Integrate with third-party APIs, banks and payment processors to ingest transactional data.
 

• Write production-quality code in Java 21 (Spring Boot) to develop microservices and data integration endpoints.
 

• Use reactive frameworks (Spring WebFlux) where needed for asynchronous processing.
 

• Operate and optimise Kafka-based streaming workflows and event-driven architectures.
 

• Implement large-scale data processing jobs on Azure Databricks with Spark (Scala/Python) to transform and aggregate data. Optimise Spark jobs for performance and cost efficiency on Azure.
 

• Design and maintain schemas in MS SQL Server and ensure data models are efficient for queries and analytics.
 

• Ensure data quality and governance: validation, schema evolution, lineage and monitoring.
 

• Expose data via APIs and data products consumed by micro-frontends and reporting tools.
 

• Embed pre-built data science solutions into the data estate.
 

• Provide Level 3 support for production issues.
 

• Collaborate closely with product, engineering and business teams to translate requirements into production-ready pipelines.
 

What we are looking for
 

• Expert in Java 21+ with Spring and Spring Boot.
 

• Hands-on experience with messaging and streaming platforms. Apache Kafka (or equivalent) experience is required – our pipelines ingest high-volume events in real time. Knowledge of Azure Event Hubs (Kafka-compatible) is also acceptable.
 

• Proficient in T-SQL with experience on MS SQL Server.
 

• Good software design and coding practices. Familiar with unit/integration testing (JUnit, Cucumber), version control (Git), and agile methodologies.
 

• Strong problem-solving, communication, and teamwork. Able to translate complex data requirements into reliable technical solutions.
 

• Eager to learn new big data and cloud technologies and keep your skills up to date.
 

• Enthusiastic about finding creative ways to solve problems and curios to explore new areas.
 

Nice-to-Have Skills
 

• Experience with big data on Microsoft Azure. Comfortable using Azure Databricks/Spark, and Azure storage (Blob/SQL/Cosmos).
 

• Exposure to Scala or Python is a plus for Spark jobs.
 

• Experience with Spring WebFlux (reactive programming) is highly desirable.
 

• Ability to containerize applications (Docker) and deploy/manage them in Kubernetes clusters.
 

• Familiar with NoSQL/database technologies; we use Cosmos DB for scalable, multi-region data.
 

• Experience with Terraform or similar tools to provision cloud resources. Familiar with CI/CD practices (we use GitOps/ArgoCD pipelines).
 

• Exposure to logging/monitoring stacks (ELK/Elastic, Prometheus/Grafana) and performance testing tools (K6, JMeter).
 

• Interest or experience in emerging AI/ML tools and LLMs (e.g. Ollama LLM) as the company explores intelligent analytics.
 

Who we are looking for
 

• Ideally someone who has worked for a Fintech start-up.
 

• Starter-finisher attitude to manage work.
 

• Strong verbal and written English communication skills.
 

• Comfortable working outside of rigid structures and frameworks.
 

• Effective working in ambiguous environments.
 

• You are a team player and can work cross-team - for instance with business-minded staff, designers, product owners, and everything in between.
 

• Actively mentors and supports others, sharing knowledge, guiding junior engineers, and contributing to a strong engineering culture.
 

• Builds alignment and influence, fostering trusted relationships and helping teams make better technical and product decisions.
 

What we stand for
 

• We believe we are better together when we listen, engage and support each other, we want you to bring your expertise and experience to work every day.
 

• We are passionate about what we are doing and want you to share this with us, enjoy your time with us, stay calm under pressure and bring positive energy to the team.
 

• We are all on a journey together, we want your ambition and flexible mind set to embrace the twists and turns as we grow as a business.
 

Your wellbeing and professional growth is important to us. If you join Pollinate, you can expect:
 

• Access to career coaching, life coaching and therapy from our employee experience partners Plumm.
 

• Access to Pluralsight for Engineering roles or a Growth Budget to develop your learning.
 

• Flexible hybrid working where our hub is used for team or collaboration meetings and company get togethers.
 

As part of Pollinate, you’ll be working with experts across payments, technology, customer experience, and financial services, supported by a world-class network of partners. Join us to be a key part of a team that’s changing the future of payments, with the freedom to make your mark. Together, we’ll push the boundaries of what’s possible with payment enabled merchant services for SMB’s around the world.
 

This Job Description covers the main areas of your responsibilities - it is not an exhaustive list.
 

About the Role:

We are looking for an experienced Senior Data Engineer to join our team and help build scalable, secure, and high-performance data platforms. In this role, you will work closely with Data Architects, Engineers, Analysts, DevOps specialists, and Data Scientists to design, develop, and optimize modern cloud-based data ecosystems.

This is a full-time remote position for a senior-level professional who can commit 40 hours per week and take ownership of complex data engineering initiatives.

Responsibilities:

As a Senior Data Engineer, you will:

* Collaborate with Data Architects on designing and implementing data solutions across Azure, AWS, or IBM Cloud environments

* Build, maintain, and optimize modern data ecosystems and data pipelines

* Develop and support data ingestion, transformation, and processing solutions

* Work closely with cross-functional teams, including Data Engineers, Analysts, DevOps Engineers, and Data Scientists

* Implement security best practices to ensure the reliability and protection of cloud infrastructure and data processes

* Apply modern engineering principles and methodologies to support business growth and innovation

* Identify opportunities to improve data quality, reliability, scalability, efficiency, and overall platform performance

* Optimize data solutions to balance performance, maintainability, and cost-effectiveness

* Design and execute unit, system, and integration testing strategies

* Contribute to continuous improvement initiatives and engineering best practices

Requirements:

* Strong commercial experience as a Data Engineer

* Advanced proficiency in Python for data processing, transformation, and analysis

* Strong expertise in SQL, including query optimization and database performance tuning

* Hands-on experience with Azure and/or AWS data platforms and services

* Experience designing and maintaining scalable cloud-based data solutions

* Solid understanding of data engineering best practices, data modeling, and ETL/ELT processes

* Experience with software development lifecycle methodologies and Agile environments

Nice to Have:

* Experience with IBM Cloud data services

* Knowledge of data governance and cloud security practices

* Experience working in enterprise-scale data environments

What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

ZentixSoft is looking for a Senior AWS Cloud Data Engineer (Financial Ecosystems) ☁️📊

We are significantly expanding our data engineering and analytics direction for our strategic international partners and are looking for a highly mature Senior Data Engineer to drive cloud-native banking data products.
 

Note: This is an Outstaffing role where you will join a high-impact core data team. 

⚠️ A Quick Note for Applicants: To move forward swiftly, your CV must clearly highlight your hands-on architecture decisions, specific AWS technologies used, data volumes, and the precise banking data products you have delivered.

💡 Why ZentixSoft? 
💸 Salary Review: A structured system of compensation reviews aligned with your expertise and engineering growth. 
🦾 Trust and Transparency: Zero micromanagement and no invasive time-trackers—we fully trust your professional autonomy. 🎁 Gifts & Culture: Corporate gifts for holidays, birthdays, and a true team atmosphere where your voice always matters.
 

If you are ready to architect resilient data solutions for a massive financial ecosystem, here is what our perfect match looks like:

1️⃣ Engineering Seniority: A proven track record of designing, building, and operating large-scale data platforms specifically within the AWS cloud environment. 
2️⃣ FinTech & Banking Domain: Solid experience handling sensitive financial data products (focused on areas like Risk, Compliance, Fraud Prevention, Finance, or Regulatory Reporting). 
3️⃣ Governance Mastery: Deep understanding of banking infrastructure needs, including strict data lineage, quality validation, auditability, and data security. 
4️⃣ Independence: Ability to make standalone architectural and technical design choices, turning raw business requirements into robust, high-volume production pipelines. 
5️⃣ Communication: Fluent English combined with strong stakeholder management skills to align easily with business, tech, and compliance teams.
 

Project Details: 
📍 Location: Primarily remote, with a preference for candidates located in the Baltics (or other EU countries). 
✈️ Work Model: Occasional onsite visits to client offices in the Baltics (approx. once per month for 2–3 days). 
⏳ Duration: Long-term cooperation. 
🚀 Start: ASAP.

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.

Join an exciting journey to create a cutting-edge Consumer Data Lake for a leading global organization based in Europe. This platform will unify, process, and leverage consumer data from various systems, unlocking advanced analytics, insights, and personalization opportunities. As a Senior Data Engineer, you will play a pivotal role in shaping and implementing the platform's architecture, focusing on hands-on technical execution and collaboration with cross-functional teams.

Your work will transform consumer data into actionable insights and personalization on a global scale. Using advanced tools to tackle complex challenges, you’ll innovate within a collaborative environment alongside skilled architects, engineers, and leaders.

Key Responsibilities:

• Hands-On Development: Build, maintain, and optimize data pipelines for ingestion, transformation, and activation.
• Create and implement scalable solutions to handle diverse data sources and high volumes of information
• Data Modeling & Warehousing: Design and maintain efficient data models and schemas for a cloud-based data platform.
• Develop pipelines to ensure data accuracy, integrity, and accessibility for downstream analytics.
• Collaboration: Partner with Solution Architects to translate high-level designs into detailed implementation plans.
• Work closely with Technical Product Owners to align data solutions with business needs.
• Collaborate with global teams to integrate data from diverse platforms, ensuring scalability, security, and accuracy.
• Platform Development: Enable data readiness for advanced analytics, reporting, and segmentation.
• Implement robust frameworks to monitor data quality, accuracy, and performance.
• Testing & Quality Assurance: Implement robust security measures to protect sensitive consumer data at every stage of the pipeline
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA ..) and internal policies.
• Monitor and address potential vulnerabilities, ensuring the platform adheres to security best practices.

Requirements:

• Over 4+ years of experience showcasing technical expertise and critical thinking in data engineering.
• Hands-on experience with DBT and strong Python programming skills.
• Proficiency in Snowflake and expertise in data modeling are essential.
• Demonstrated experience in building consumer data lakes and developing consumer analytics capabilities is required.
• In-depth understanding of privacy and security engineering within Snowflake, including concepts like RBAC, dynamic/tag-based data masking, row-level security/access policies, and secure views.
• Ability to design, implement, and promote advanced solution patterns and standards for solving complex challenges.
• Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure).
• Practical experience with Big Data batch and streaming tools.
• Competence in SQL, NoSQL, relational database design (SAP HANA experience is a bonus), and efficient methods for data retrieval and preparation at scale.
• Proven ability to collect and process raw data at scale, including scripting, web scraping, API integration, and SQL querying.
• Experience working in global environments and collaborating with virtual teams.
• A Bachelor’s or Master’s degree in Data Science, Computer Science, Economics, or a related discipline.

We are looking for a Lead Data Engineer to drive the design and implementation of scalable data solutions, pipelines, and analytics-ready datasets. 

What You’ll Do 

• Lead design and implementation of data pipelines, transformations, and curated datasets 
• Translate business requirements into structured data solutions and models 
• Guide and execute development of reusable, analytics-ready data assets 
• Ensure consistency in how key data elements are defined and used across systems 
• Collaborate with stakeholders to define and refine data requirements and logic 
• Review and guide engineering work to ensure quality, performance, and scalability 
• Establish best practices for data engineering, transformation, and data quality 
• Support integration of data across multiple domains and systems 
• Contribute to architecture decisions across data platforms and tooling 
• Mentor and support other engineers on the team 

What You Bring 

Must-Haves 

• 5+ years of experience in data engineering, analytics engineering, or related fields 
• Strong SQL expertise and experience designing complex data transformations 
• Hands-on experience with modern data platforms (e.g., GCP BigQuery, Databricks, Snowflake) 
• Data platforms experience. ELT or ETL, orchestration such as Airflow or dbt, Spark, data warehouses and lakehouses such as Snowflake, BigQuery, or Databricks, streaming such as Kafka or Kinesis, metadata and data quality 
• Proficiency in Python 
• Strong understanding of data modeling concepts and data structuring for analytics 
• Experience working with stakeholders to define requirements and deliver data solutions 
• Ability to balance hands-on delivery with technical guidance 

Nice-to-Haves 

• Familiarity with data governance, lineage, or metadata management concepts 
• Experience working with cross-domain data (e.g., customer, product, transactions) 
• Exposure to financial services or other data-intensive industries 
• Experience supporting migration or evolution of data platforms (e.g., toward Databricks) 
• Experience with orchestration tools (e.g., Airflow, Cloud Composer) 
• Exposure to data modeling concepts (e.g., dimensional models, data marts, reusable datasets) 

What’s in It for You 

• Impact at scale. Help shape enterprise AI, software, and data programs across industries. 
• Growth and mastery. Work with a seasoned team from leading consulting and technology backgrounds. 
• Build real products. Work on production ready assets with autonomy over key technical decisions.