Top Data Engineer Jobs in Berlin

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.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Lead technical vision and architecture for enterprise data platforms. Own end-to-end platform design from ingestion to distribution, set engineering standards, mentor senior engineers, and collaborate with security, compliance, product, and stakeholders to deliver scalable, reliable, and compliant data platform capabilities.

Design and scale mission-critical market data services for stocks, options, crypto, and foreign exchange. Responsibilities include architecting backend systems and APIs, maintaining software quality and test coverage, participating in code reviews, and troubleshooting incidents and bugs. The role uses Go and Python with REST, gRPC, WebSockets, SSE, Docker, Kubernetes, Google Cloud, BigTable, Prometheus, Grafana, and ELK.

Design, build, and operate scalable data infrastructure on AWS and Kubernetes. Develop streaming and platform components (Kafka, Snowflake), implement IaC (Terraform) and CI/CD (GitLab), build monitoring/observability, own features end-to-end, collaborate with analysts and data scientists, and participate in on-call rotations to ensure platform reliability and performance.

Lead design and implementation of customer-facing data intelligence applications: build shared API layers, low-latency data-access and caching strategies, advanced interactive visualizations, LLM-enabled interfaces, and mentor engineers while shaping architecture and standards.

Design, build, and operate scalable real-time and batch data processing systems. Own features end-to-end, make architectural decisions, ensure production reliability and observability, collaborate cross-functionally, write high-quality tested code, and mentor junior engineers.

Lead design and implementation of scalable, real-time data infrastructure. Build and optimize production-grade streaming pipelines, employ spec-driven development and agentic AI workflows, implement testing/monitoring, take ownership of systems, and mentor junior engineers.

Design, build, and scale high-performance data pipelines and infrastructure (ingestion, transformation, storage, modeling, serving) using ClickHouse, Postgres, Python and dbt. Manage data quality, reliability, and observability at terabyte and 500M+ address scale, collaborate with researchers and product, mentor engineers, and leverage AI tools to accelerate work.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

Own and evolve the end-to-end customer identity resolution pipeline, improve probabilistic matching models, build scalable BigQuery/GCS/Cloud Run data pipelines, add monitoring and validation, and collaborate with stakeholders to deliver reliable, production-grade identity master data.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.