Senior Manager, Data Engineering (m/f/d)

SHAPE THE FUTURE OF PRIVACY WITH USERCENTRICS

Usercentrics is a global leader in data privacy and privacy-led marketing solutions. We believe there is no need for a trade-off between growth and privacy compliance. Our vision is to unlock the potential of data privacy to empower a thriving digital ecosystem. We work with companies to create a healthy balance between data-driven business and privacy-led marketing for every size of enterprise. Our customers build trust with their users through improved transparency and control to drastically improve marketing and monetization, while achieving full privacy compliance.

We are looking for a Senior Manager, Data Engineering to lead and scale our Data Engineering team. This role owns the data platform and integration architecture end to end, combining strategic leadership with hands-on, player-coach expertise in data engineering, ensuring our data ecosystem is trusted, reliable, well-governed, and optimized for business impact as our SaaS business scales.

You will shape our long-term data platform and DataOps strategy. Initially, you will lead the modernization of our data platform, working closely with Engineering, Product, Analytics, Commercial, and Finance to deliver optimal pipelines and reliable, well-governed integrations with the operational systems and third-party tools that run a modern SaaS company. Over time, you will design and lead the evolution of the platform toward advanced use cases such as ML Ops, Data Products, and real-time analytics, while growing a small team of Data Engineers into a fully-fledged data platform team.

The challenge

Our data is complex. It is high-volume, multi-source, time-sensitive, and often messy. The challenge is to build a data engine that is:

• Trusted: accurate, governed, explainable;
• Fast: optimized performance and cost, low latency where it matters;
• Composable: clean models that scale with new products;
• Self-serve: enables Product, Analytics, and GTM teams;
• Reliable: observable, resilient, and operationally excellent.

Your Tasks

• Lead a team of Data Engineers as a hands-on player-coach, growing it into a fully-fledged data platform team with clear ownership and ways of working, and helping it balance strategic priorities with operational excellence.
• Own the data warehousing strategy end to end, the stack, the architectural principles, and where the platform goes next as our SaaS business scales, ensuring schemas, storage patterns, and partitioning choices deliver performance and cost efficiency across very different workloads.
• Set the strategy and architecture for connecting our data platform to the operational systems and third-party tools that run a modern SaaS company, delivering high-quality systems with reliable, well-governed data flows.
• Raise the bar on data ingestion and enrichment, defining what "good" looks like for reliability, data quality, and fault tolerance across batch and near-real-time pipelines, and design and evolve the foundational data layers that power everything downstream: integrations, operational reporting, and advanced analytics.
• Own platform governance (access control, data classification, retention, auditability) aligned with security and privacy requirements, and build real observability into pipelines, datasets, and integrations: freshness, volume anomalies, quality signals, and cost.
• Partner cross-functionally, communicating clearly with stakeholders on tradeoffs, risks, and timelines, and influence the broader organization on data quality, trust, and accountability.