Top Data Engineer Jobs in Warsaw

The Senior Data Engineer will design, build, and maintain data systems, pipelines, and infrastructure for data processing and analysis, collaborating with stakeholders and ensuring data quality.

The Data Engineering Lead is responsible for designing and optimizing data architectures, overseeing data systems, mentoring team members, and ensuring high-performance data processes that align with business goals.

The Senior Data Engineer will design and maintain data systems, build data pipelines, optimize ETL processes, and ensure data quality, collaborating with various teams to facilitate data-driven decision making.

Design and implement scalable batch and streaming data pipelines on Databricks and cloud platforms; build data transformations, CI/CD and MLOps practices; collaborate with data scientists; create data governance, monitoring, and Power BI visualizations; translate business requirements into performant technical solutions.

Build and maintain scalable batch and streaming data pipelines using Databricks, Spark, Airflow/Dagster and DBT; implement CI/CD and DevOps practices; support ML projects and Power BI reporting; translate business requirements into performant data solutions.

Design, build, and maintain scalable data pipelines and platforms for batch and streaming data using Spark, Airflow, Iceberg, and cloud services. Optimize ingestion, processing, and storage, collaborate with stakeholders, monitor platform performance, and write high-quality Python/Java/Scala code to support enterprise reporting and analytics.

As a Data Engineer, you will lead data initiatives, build scalable ETL pipelines, ensure data quality, and collaborate with teams to drive data-driven decisions.

Design, build, and maintain scalable data pipelines; integrate diverse data sources into warehouses or lakes; collaborate with data scientists and engineers to ensure quality and availability; optimize schemas, models, and performance; implement governance, security, and compliance; monitor reliability and document systems.

Lead technical data strategy and architecture for Navify Cervical Screening. Drive data integration, governance, and large-scale pipeline design; mentor engineers; evaluate new technologies; ensure compliance, quality, and timely delivery of data requirements across cross-functional teams.

The role involves designing scalable data pipelines and architectures, integrating multiple data sources, and ensuring data quality and governance within the CMDB and Asset Intelligence platform.

The Database Engineer will develop and optimize SQL queries, design data models, maintain ETL processes, and ensure data integrity while supporting analytics and reporting for the company's SaaS solution.

As a Data Engineer, you will develop and support big data processing pipelines, build cloud-based infrastructure, and provide visualization solutions for data assets.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

This role supports Supply Chain operations by improving data quality, managing data transformation, and designing data models for visualization.

The Senior Software Engineer will lead engineering teams, mentor junior engineers, and ensure system reliability and performance while developing backend services.

Design, implement and govern HR data pipelines and processes to ensure group-wide People & Culture data consistency. Support system migration and data alignment, analyze large datasets for inconsistencies, document mappings and playbooks, and communicate findings to non-technical HR stakeholders. Work closely with Group HR Controller, country HR Heads, project teams and technical teams to enable accurate HR reporting and compliance with GDPR.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

As a Leading Data Engineer, you will manage a team delivering customer data solutions using Snowflake, ensure platform reliability and compliance, and drive engineering best practices.

The AI Data Engineer will develop and maintain AI data pipelines, ensure system reliability, and innovate within AI technologies.

Design, build, and operate scalable data lake and streaming pipelines (batch and real-time) using Spark, Databricks, and Kafka. Ensure data quality, observability, CI/CD, and integration with SQL/NoSQL stores and cloud platforms to deliver reliable data products for analytics and ML.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

The Full Stack Data Engineer will design and build scalable data pipelines, optimize Snowflake architecture, develop dashboards and analytics solutions, and collaborate with cross-functional teams to ensure data reliability and meet business requirements.

As a Data Engineer, you'll design and maintain scalable data pipelines and analytics solutions in GCP, focusing on LLM usage analytics, data transformation, and collaboration with teams to ensure high-quality data processing.

The Data Engineer will develop, maintain, and optimize data pipelines using Apache Airflow, manage database performance, and support Elasticsearch integration. Responsibilities include building ETL scripts, handling Unix/Linux operations, and implementing CI/CD pipelines in GitLab.