Top Data Engineer Jobs in Munich

The Data Engineer will own the data stack, develop cloud-based data platforms, maintain data pipelines, and support data-driven decision-making within the company.

Responsible for deploying and maintaining data center infrastructure, troubleshooting hardware and network issues, managing inventory, and setting up data centers.

The Data Engineer will develop scalable data processing solutions, facilitate data ingestion, and ensure data quality while mentoring junior engineers.

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.

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, model, and develop AWS-based data ecosystems and pipelines. Gather and document business and technical requirements, optimize data storage (lakes/warehouses), tune performance, troubleshoot processing and infrastructure issues, integrate diverse data sources, mentor junior engineers, and engage directly with clients.

Design, build, and operate scalable data systems and ETL pipelines for research and live trading. Transform raw data into reliable datasets, collaborate with researchers, manage storage systems, and maintain production observability and performance.

The role involves analyzing data for insights, creating dashboards, and collaborating with teams to optimize product performance using SQL, Python, and visualization tools.

Build, optimize, and maintain data pipelines and data systems using Python and PySpark. Evaluate and annotate AI-generated ETL outputs, ensure data accuracy and scalability, integrate data solutions with software teams, document processes, follow data governance, and support backlog and best practices under senior guidance.

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.

The Finance Data Engineer will design and deploy automated pipelines, ensure finance data integrity, and implement AI-driven solutions while maintaining data sovereignty and compliance with government contracts.

Join the AI & Biometrics team to develop a resilient data platform for machine learning, focusing on data ingestion, transformation, and secure API development.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

Lead technical solution architecture and application engineering for data center automation using robotics and partner technologies. Support presales, shape proposals, drive system integration, and ensure smooth transition from concept to execution. Capture feedback to improve standardized solutions and contribute to next-generation, AI-enabled automation concepts.

Architect and build a greenfield data warehouse, develop resilient ETL/ELT pipelines, ensure data integrity, and lead junior engineers. Work on modern data infrastructure with a focus on AI integration.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

The role involves data collection to support AI model training, managing cloud infrastructure on GCP, and improving data ingestion processes.

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.

Build and maintain scalable data pipelines, transformations, and analytics-ready models using dbt, SQL, Python, and Snowflake. Implement ingestion, CDC, API integrations, testing, monitoring, and observability. Collaborate with analysts and stakeholders to define metrics, ensure data governance and compliance, and optimize data platform reliability.

Develop and integrate software for data processing and visualization to support engineering teams. Guide junior engineers, create web applications, and improve performance.

Own and evolve Enode's data platform and pipelines to support the Flex product: build reliable datasets, ensure data quality and monitoring, enable self-serve analytics, and partner with data science on feature pipelines and model readiness. Drive pragmatic platform improvements, documentation, and tooling to scale data reliability and trust across delivery, billing, and reporting.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.

Design and maintain scalable data pipelines and platforms, lead migration from Snowflake to client service, propose improvements, drive initiatives, and collaborate with senior engineers, product/project managers, and data analysts.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.