Lead Data Engineer

About the company

Biorce is a pioneering Healthtech company dedicated to revolutionizing drug development through the power of AI. We are passionate about accelerating medical advancements and improving patient outcomes.

Our team comprises seasoned clinical research professionals, data scientists, and AI experts, working collaboratively to bridge the gap between cutting-edge technology and real-world clinical needs.

With an unwavering commitment to revolutionize healthcare, we envision a world where all patients benefit from accelerated and cost-effective access to treatments. Biorce is poised to redefine the landscape of healthcare, shaping a future where innovation and accessibility converge for the betterment of humanity.

About the role

We are seeking a Data Engineering Lead to head our data engineering team and serve as the department lead for our Barcelona hub. This is a senior, technical leadership role, a player-coach who is credible in architecture and code, but whose primary job is to build, grow, and multiply a high-performing team.

Biorce runs data engineering across two hubs, Barcelona and Austin keeping those teams working as one is central to this role. You will be the face of data engineering in Spain: the person who represents the function locally, builds our presence and employer brand in the Barcelona market, and partners closely with the Austin team to keep architecture, standards, and roadmap in sync across sites and time zones.

You will own the people, delivery, and health of the data engineering function at the Barcelona site: hiring and developing engineers (including senior ICs / Data Architect), driving execution against the platform roadmap, and setting the standards and culture, including how we responsibly adopt AI-first, agentic ways of working. You will be the connective tissue between the engineers building the platform and the data science, AI, MLOps, product, and clinical stakeholders who depend on it.

This is a rare chance to stand up and lead a team building a next-generation clinical data platform from the ground up, at the heart of our growing European presence.

Who We're Looking For

An experienced engineering leader who has led data or platform teams and still speaks the language fluently, someone engineers respect technically and want to work for. You care about people first, but you never lose sight of delivery, quality, and the realities of regulated clinical data. You are energized (not threatened) by an AI-first shift, and you know how to bring a team along through change.

You are equally comfortable running a 1:1, unblocking the mapping of a stubborn dataset into the common data model, defending a roadmap to leadership, and coaching an engineer on how (and when not) to trust a coding agent.

Key Responsibilities

People Leadership

• Lead, coach, and grow the Barcelona data engineering team including senior ICs and the Data Architect, through regular 1:1s, feedback, and career development.
• Work with the Head of Data to design hiring for the team: define roles, run a high-quality and fair interview process, and build a strong, diverse pipeline.
• Set clear expectations and run a fair, transparent performance and growth process; retain and develop top talent.
• Foster a healthy, inclusive, high-trust team culture as the on-site department lead.

Delivery & Execution

• Own delivery of the data engineering roadmap. Planning, prioritization, and predictable execution against platform milestones.
• Establish lightweight, effective engineering processes (agile/iterative delivery, code review, on-call/incident response, documentation standards).
• Track and communicate progress, risks, and trade-offs to Data / AI leadership and cross-functional stakeholders.
• Balance speed of iteration with the reliability and compliance demands of clinical data.

Technical Direction (Player-Coach)

• Partner with the Data Architect to set and uphold technical standards for the hybrid open-source + Databricks + dbt on GCP platform.
• Provide credible technical guidance in design and architecture reviews; stay close enough to the work to make good calls and unblock the team.
• Champion quality: data reliability, lineage, observability, testing, and cost-efficiency (FinOps).

AI-First Culture & Adoption

• Drive responsible adoption of AI-first, agentic data engineering across the team, Claude Code, coding agents, and the self-healing/agentic warehouse vision.
• Establish team norms, guardrails, and review practices so AI-assisted work is fast and validated to clinical/regulated standards.
• Measure and improve how AI leverage translates into team velocity and quality.

Cross-Hub Collaboration & Local Leadership