Top Data Engineer Jobs in Warsaw

The Data Engineer will design, build, and maintain scalable data pipelines, develop ETL workflows using Python and SQL, and optimize data processes to ensure reliability and performance.

The Data Analytics Engineer will design and maintain data pipelines, automate workflows, develop BI tools, and collaborate with teams to deliver impactful analytics.

The Analytics Engineer will design and implement data integration solutions (ETL) for data analytics, build data models, and improve data infrastructure.

Lead a data engineering team, develop AI self-service portal and data pipelines, interface with internal teams, and ensure software engineering best practices.

The Senior Data Engineer will design and maintain scalable data pipelines, ensuring secure and timely data delivery for analytics and AI applications.

The Data Engineer will design, optimize, and implement data pipelines and solutions using Apache Airflow, Snowflake, and Kafka, ensuring data accessibility and reliability.

The Principal Data Platform Engineer will design and implement scalable data platforms, lead engineering initiatives, mentor teams, and ensure data governance and discoverability.

The Senior Data Platform Engineer at Moderna is responsible for advancing data platform capabilities, implementing robust data services on AWS, enhancing platform functionalities, and collaborating with different teams to ensure secure data access and management.

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

Design and maintain data pipelines, ensure data reliability, structure data systems, and manage software development processes while collaborating in a team.

Build, maintain, and scale ELT data pipelines and dbt models on Google BigQuery. Write Python for data processing, ensure data quality, monitor pipelines, collaborate with analytics/product/game teams, and contribute to data architecture in a fast-paced startup.

Design, build, and maintain ELT pipelines; develop, test, and document dbt models; optimize and query Google BigQuery; write Python for data processing; ensure data quality and reliability; monitor and troubleshoot pipelines; collaborate with analytics, product, and game teams and influence data architecture.

Develop and own core product components for tape storage and ransomware detection. Design and implement business logic, add features, work with databases, contribute to architecture, and solve low-level multithreading and performance challenges.

Design, build, and maintain backend services, REST APIs, databases, and near-real-time and batch data pipelines. Develop a query engine and scalable insights pipelines, collaborate with product and engineering, improve legacy code, and ensure production monitoring, alerting, and tooling for support.

Develop software for risk data pipelines, collaborating with trading teams to manage trade data, improve capital efficiency, and automate operations.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Design, build, and maintain large-scale batch and real-time data pipelines for high-volume advertising data using Java/Scala/Python with Spark and Flink. Ensure data quality, optimize performance, improve observability, integrate external sources, and contribute to platform architecture and cross-team design reviews.

Design and implement the Price Optimizer decision logic: translate pricing rules into mathematical models and production-ready Python code, refine simulation and optimization algorithms, write tested maintainable code, validate model behavior, and collaborate with Solution Architects and Data Engineers to integrate into Dagster pipelines.

The Senior Data Engineer will design and optimize scalable data pipelines using Snowflake, ensuring data quality and mentoring junior engineers while implementing best practices.

Build and maintain Python-based data pipelines on Databricks, collaborate with product and domain experts, debug Tier-2 system issues, create documentation and onboarding processes, write integration tests, manage code in GitLab, and improve data quality and self-service tooling.

Design, build, and own streaming data pipelines and feature stores to enable low-latency inference and real-time model serving. Partner with ML and infra teams to define data contracts, ensure data quality, observability, and SLAs, and move batch pipelines toward real-time production. Evaluate streaming and feature store technologies and contribute to inference pipeline tooling.

Build and maintain real-time streaming data pipelines and feature stores to power low-latency model inference. Collaborate with ML and AI infra teams on data contracts, observability, and SLAs; drive batch-to-real-time migrations and evaluate emerging streaming/feature store technologies.

Seeking a Senior Data Support Engineer with 5-6 years of experience in Data Engineering, specifically utilizing Snowflake, Python, SQL, and AWS for data manipulation, warehousing, and testing processes.