Top Data Engineer Jobs in Warsaw

As a Data Engineer, you will lead the development of scalable data pipelines, manage production datasets, and mentor engineers while collaborating with Data Science and Analytics teams.

As a BI Data Engineer, you'll develop scalable data solutions, maintain ETL pipelines, ensure data integrity, and collaborate across teams for insights and reporting.

The Senior AI Data Engineer will lead the development of data infrastructure for AI projects, ensuring scalable data pipelines and governance, while collaborating with the AI team to optimize performance and facilitate AI training and operations.

The Junior Data Processing Engineer will assist in data pipeline operations, troubleshooting, and collaborating with stakeholders while gaining hands-on experience in data processing on Azure.

The role involves creating commerce intelligence solutions using AI to enhance decision-making processes in a digital commerce environment.

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

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

As a Data Engineer at Xebia, you will design and maintain data platforms, implement cloud architectures on GCP, build ETL solutions, and manage data workflows using Apache Airflow and Spark, alongside CI/CD pipelines.

The Data Engineer will design and maintain data pipelines, optimize ETL processes, ensure data quality, and collaborate in an agile environment.

The role involves building and operating scalable distributed systems, developing RESTful services, and supporting data movement needs across Netflix.

Design, build, and maintain data pipelines to support AI/ML initiatives. Collaborate with teams to optimize data processes and ensure data quality.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

Design, implement, and deploy ML and AI solutions; architect AI systems; build and oversee data pipelines; collaborate with engineering teams; translate business needs to data problems; present results to stakeholders; follow Agile practices.

Lead design and delivery of end-to-end ML/AI solutions: architect systems, implement and validate models, oversee data pipelines, coordinate cross-functional teams, mentor engineers, liaise with clients, and ensure timely Agile delivery.

As a Lead Python Engineer, you will build a multitenant data platform and data ingestion pipelines on AWS, collaborating with various teams and improving processes.

The Lead Data Engineer will develop enterprise-level data pipelines, oversee data lifecycle management, and provide technical leadership while ensuring data security and compliance.

Design and maintain scalable data pipelines, improve data processes, collaborate on algorithms, and ensure reliable delivery of internal data products.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.

As a Principal Big Data Engineer, you will design scalable solutions, develop data pipelines, create features, and collaborate with various teams to enhance Akamai's data platform.

The role involves managing and transforming high volume data to solve business issues related to fraud and compliance, using big data technologies while working in Agile sprints and collaborating with various stakeholders.

The Lead Data Engineer at Roche will design and build scalable data solutions, mentor team members, and ensure high-quality delivery of data engineering projects, while collaborating on AI-enabled ecosystems.

Design, build, and maintain scalable GCP data pipelines and ETL/reverse ETL processes using Dataflow, Dataform, and BigQuery. Develop secure APIs for ingestion, optimize data models and Datastream integrations, implement monitoring, and ensure GDPR/CCPA-compliant data governance for player analytics and fraud detection.

As a Data Engineer II, you will design scalable data pipelines in AWS, develop SQL transformations, and enhance MLOps workflows, focusing on analytics and machine learning initiatives.

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

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.