Sr EM Data Platform

We are looking for a Senior Engineering Manager to lead and scale our Data Engineering function. This role has end to end ownership of the data platform and integration architecture. It combines strategic leadership with hands-on expertise in data engineering, ensuring that our data ecosystem is secure, reliable, and optimized for business impact.

As Senior Engineering Manager, you will shape the long term DataOps strategy. Initially, you will oversee the modernization of our data platform and work closely with Engineering, Product, and Analytics to ensure optimal pipelines and reliable integrations with operational systems and third party tools. Over time, you will design and lead the evolution of the Data Platform to support advanced use cases such as ML Ops, Data Products, and real time analytics.

YOUR TASKS

• Initially lead a small team of Data Engineers, providing hands on technical leadership, and progressively scale it into a full data platform team with clear ownership and operating model
• Own the data warehousing strategy, including the technology stack, core architectural principles, and long term evolution
• Define and lead the strategy and architecture for integrating the data platform with operational systems and third party tools, ensuring reliable, scalable, and well governed data flows across the organization.
• Define standards for data ingestion and enrichment, covering reliability, data quality, and fault tolerance across batch and near real time pipelines
• Lead the design and maintenance of foundational data layers that support multiple downstream use cases, including integrations, operational reporting, and advanced analytics
• Ensure warehouse schemas, storage patterns, and partitioning strategies support performance, scalability, and cost efficiency across diverse workloads
• Oversee the data platform governance, including access control, data classification, retention policies, and auditability, aligned with security and privacy requirements
• Drive observability for pipelines, datasets, and integrations including freshness, volume anomalies, data quality signals, and cost monitoring
• Enable the team to balance strategic priorities with operational excellence.

Do you have experience in APIs?, Hybrid in Munich (minimum of 2-3 days a week from the office), * Proven experience defining long term data platform and DataOps strategies, translating business and technical requirements into scalable architectures

• Hands on background in data engineering, with the ability to guide technical design decisions, review implementations, and unblock complex engineering problems
• Deep understanding of data integration patterns with operational systems and third party tools, including APIs, event driven architectures, CDC, and reverse ETL use cases
• Solid grasp of data quality, reliability, and fault tolerance principles, including idempotency, error handling, and recovery strategies
• Experience designing and operating enriched data layers that support multiple downstream use cases across analytics, integrations, and advanced data products
• Strong knowledge of data governance, security, and privacy concepts, including access control, data classification, retention, and auditability
• Practical experience with observability and monitoring of data platforms, covering pipeline health, freshness, data quality signals, and cost awareness
• Ability to lead and grow engineering teams, starting with a small group of data engineers and scaling into a broader data platform or DataOps team
• Clear communicator with strong stakeholder management skills, able to align Engineering, Product, Analytics, and Business Systems around shared ownership and priorities
• Comfortable operating in ambiguous environments, balancing short term delivery with long term platform evolution and architectural integrity
• Experience defining operating models, ownership boundaries, and on call responsibilities for data platform teams

4.74.7 out of 5 stars München Hybrid work Permanent, Full-time, Pulled from the full job description

• Flexible schedule

Usercentrics is a global market leader in the field of Consent Management Platforms (CMP). We enable businesses to collect, manage and document user consents on websites and apps in order to achieve full compliance with global privacy regulations while facilitating high consent rates and building trust with their customers.

Usercentrics believes in creating a healthy balance between data privacy and data-driven business, delivering solutions for every size of enterprise. Cookiebot CMP is our plug-and-play SaaS for smaller businesses and organizations, App CMP handles user consent on mobile apps, and Usercentrics CMP serves companies with enterprise-grade custom requirements for unifying consent and data from capture to processing.

Helping clients like Daimler, ING Diba and Santander achieve privacy compliance, Usercentrics is active in more than 100 countries, with 2000+ resellers and handles more than 61 million daily user consents.

Visit usercentrics.com and cookiebot.com to learn more.