Team Lead - Data Platform

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ABOUT AMBOSS

AMBOSS is the copilot for medical professionals, empowering them to provide the best possible care through our learning and clinical decision support tool. Our team brings together care, innovative thinking, and cutting-edge AI medical technology. Our founders launched AMBOSS in 2012 with the goal of creating a tool they wished they had during medical school and clinical practice. Since then, we've grown to over 600 employees and are active in over 180 countries - primarily in Germany and the US. Our offices are located in Berlin, Cologne, New York, Cagliari and Cape Town.

Want to learn more about our culture? Watch our video https://youtu.be/gTPDn5XpeJgto explore what makes us unique

WHY DATA & ANALYTICS AT AMBOSS?

Join a high-trust, cross-functional team where data sits at the heart of every product decision, commercial bet and operational process. You will work side-by-side with our Analytics team, Product, Engineering, Commercial, Medical and Operations colleagues to turn a modern, cloud-native stack (GCP/AWS, BigQuery, Airflow, Airbyte, dbt, Looker, Mixpanel, Claude Code) plus a growing set of integrations and internal tools into reliable insights that move the business forward. Your work will guide decisions that reach medical students and clinicians worldwide, directly advancing our mission to enable all medical professionals to provide the best possible care.

ROLE OVERVIEW

As Data Platform Lead you will be the people manager of a small, senior team and the domain expert steering AMBOSS's end-to-end data platform strategy. That said, the role is broader than a classic data platform mandate. Beyond owning platform evolution and pipelines, you and your team also own the integration layer to our ERP and other core business systems. On top of that you build small services and internal tools that solve specific business and operations problems. One current example is our master data management service for medical institutions around the world, which powers B2B commercial work and product experience.

This role is more dynamic and more business-forward than a pure engineering leadership position. Communication with stakeholders across Commercial, Product, Finance, Operations and Medical is constant. Engineering excellence still matters, but coordination, prioritization, fast judgement calls and a strong hands-on mentality matter at least as much.

YOU WILL:

- Set the course. Own and sequence the roadmap across the data platform, ERP and business systems integrations, plus the internal tools and services your team builds and runs.

- Own the Single Source of Truth for the entire company so Analysts, Scientists and stakeholders across departments speak the same data language and use the same metrics.

- Develop the team. Hire, mentor and grow 3 to 5 Data Engineers. Run clear goal-setting and feedback cycles.

- Architect for scale. Design and review core components: batch and real-time pipelines, modeling layers, integrations, governance, observability and CI/CD so Analysts, Data Scientists and other Engineering teams can self-serve with confidence.

- Build internal services and tools to unblock the business. Our master data management service for medical institutions is one example. Expect more of these as the business grows.

- Partner with Commercial, Finance, Product, Operations and Medical. Translate ambiguous business needs into systems and data products that move the company forward.

- Navigate ambiguity and stay hands-on. Create structure where there is none, sequence the work pragmatically and make the call when there is no obvious right answer. This is not a step-back-and-review-PRs role. You will be in the work alongside your team on the highest-leverage problems.

- Raise the bar. Codify engineering standards for code quality, testing, reliability and incident response. Scale agentic coding and AI-assisted workflows so a small team can punch above its weight.

- Stay tool-agnostic: evaluate, pilot and when needed retire technologies based on evidence rather than hype.

YOU BRING:

- 5+ years in data engineering or data platform roles, including 2+ years leading projects or people.

- Deep SQL and strong Python. Production experience with Airflow, dbt or comparable frameworks.

- Hands-on expertise with cloud warehouses (BigQuery, Snowflake) and at least one major cloud provider (AWS or GCP).

- Proven CI/CD and IaC chops (GitHub Actions, Terraform or similar).

- Solid grasp of data modelling, governance and observability patterns.

- Experience integrating with or building against business systems such as ERP, Shop or even Bank integrations. You are comfortable owning that layer end to end.

- A track record of working closely with Commercial, Finance, Operations or Analytics stakeholders and treating them as first-class partners.

- A bias to action in ambiguous situations. You would rather make a reasonable call and adjust than wait for perfect information.

- Hands-on fluency with agentic coding AI tools (like Claude Code) and a track record of using AI to accelerate engineering work.

- Excellent English communication. German is a plus.

- Bonus: exposure to AI/LLM workloads or vector databases on the production side.

YOU ENJOY:

- Operating in a fast-moving, ambiguous environment where the plane gets built while you are flying in it. You like being pragmatic and bringing in structure without slowing the business down.

- Coordinating across many stakeholders. You move easily between an engineering deep-dive in the morning and a Commercial leadership conversation in the afternoon.

- Staying hands-on as a leader. You are happy to write SQL, debug an integration or scope an internal tool yourself when that is what the situation calls for.

- Translating between worlds. You take messy business problems and turn them into clear technical scope. You take technical trade-offs and turn them into concise narratives…