Top Data Engineer Jobs in Berlin

Lead design and implementation of scalable data architectures, pipelines and Data/AI features. Build reliable data warehouses and ETL, enable analytics, and collaborate with product, analysts and supply chain specialists to deliver optimized, production-ready solutions.

The Senior Full Stack Engineer will manage data operations, design scalable data pipelines, optimize data warehouses, and ensure data quality across platforms while collaborating with stakeholders.

Design and implement search retrieval and ranking systems, build data pipelines, and evaluate performance metrics. Collaborate with teams to enhance system relevance.

As a Data Platform Engineer, you will design, build, and maintain a cloud data platform, ensuring its reliability and efficiency while supporting AI integration and collaboration with internal teams.

The Senior Data & Financial Analytics Engineer will design data solutions, analyze financial metrics, partner with finance teams, and ensure data governance.

The Data Ops Engineer will design and build data pipelines, develop automated systems for insights delivery, enable AI workflows, and optimize data strategy.

You will design and build data infrastructure from scratch, enabling the company to utilize data effectively across all teams, ensuring security and regulatory compliance.

As a Senior Data Engineer, you'll design and maintain Python-based data pipelines for ML workflows, ensure data quality, and collaborate with various teams to enhance fraud detection systems.

As an Applied ML Engineer, you will build and scale data pipelines for video generation, ensuring data quality and optimizing preprocessing workflows.

Build and operate Python/PySpark production data pipelines (including near real-time), ensure data quality, create core data models and reporting pipelines for AML/Risk, support regulatory reporting and data governance, and collaborate with cross-functional teams to deploy scalable, auditable data solutions.

As a Big Data Engineer, you will design and implement data processing systems, manage technologies like Hadoop and Spark, and build ETL processes to ensure data quality and performance.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Design and develop scalable data pipelines using PySpark and Databricks, focusing on data ingestion, transformation, validation, and performance optimization.

The Lead Data Engineer will design and build scalable data pipelines on Databricks, develop ETL/ELT pipelines with PySpark, and mentor engineering teams for data transformation and analytics.

Design, build, and operate data ingestion pipelines and cloud platform infrastructure (GCP). Ensure data quality, privacy/GDPR controls, and prepare governed datasets for ML/AI. Maintain orchestration, CI/CD, monitoring, and mentor engineers while evaluating new technologies and AI-enabled platform services.

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

As a Senior Data Engineer, you will design scalable data pipelines, implement new technologies, collaborate with Data Scientists, and lead technical aspects while maintaining documentation on data processes.

This role involves data collection for model training, operating cloud infrastructure, and collaborating with AI teams to enhance data quality and throughput.

Design and develop data models, ETL processes, and cloud-based data solutions using Azure and various big data technologies. Support report generation and data analysis.

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

The Senior Data Engineer will design scalable systems, automate ML operations, optimize performance, and enhance infrastructure for data processing and monitoring.

The Staff/Lead Fullstack Engineer will enhance the Mimica Webapp by architecting scalable UI components, managing large datasets, and optimizing performance while collaborating with cross-functional teams.

Design and build reliable, performant data pipelines for large payment datasets. Own end-to-end data flows, drive data quality, implement transformations (dbt), operate on StarRocks and Flink/Spark in cloud (AWS/GCP), collaborate cross-functionally, establish engineering standards, mentor engineers, and shape CI/CD and incident practices.

Lead end-to-end data engineering for supply-side products: build reliable pipelines, data models and observability; partner with Supply, Product and Data; improve production systems; mentor engineers and shape best practices for scalability, quality, performance, and cost-efficiency.

As a Senior Data Engineer, you'll design and maintain data pipelines, transform raw data into insights, and support multiple teams with reliable data analytics.