Lead Data Engineer

At EarlyTracks, we empower care institutions to manage high-quality medical records with greater efficiency. Our solutions are built on cutting-edge Natural Language Processing (NLP), combining machine learning, terminological resources, and intelligent interfaces to transform unstructured medical data into actionable insights.

About the team

Our Data Engineering team builds the standards-based health data layer connecting hospital systems, clinical applications and new AI-driven use cases. The team develops FHIR repositories, ingestion and transformation pipelines, APIs, interoperability services and data-governance mechanisms. Its work turns fragmented clinical information into structured, interoperable and reusable data. Data Engineering works closely with our Terminology and Data Science teams, combining FHIR, SNOMED CT, NLP and automated data-quality management. The team addresses real-world challenges around provenance, security, reconciliation and federated exchange of health data.

About the job

As a Data Engineering Lead, you will play a key role in shaping and delivering our healthcare data products. You will combine hands-on technical expertise with team leadership responsibilities, ensuring development efforts stay aligned with product priorities, customer commitments, and technical sustainability.

You will serve as the technical reference point for decisions within the Data Engineering domain, and act as the operational bridge between the Product Lead, the Operations Manager, and the development team.

Your mission is to turn ambitious product vision into fast, scalable, high-quality execution, maximizing customer value without compromising technical excellence.

Key Objectives

• Lead and develop the Data Engineering.
• Translate product priorities into actionable technical work.
• Maintain and prioritize the operational backlog in Jira.
• Ensure high standards of software quality, testing, and documentation.
• Balance product roadmap objectives with delivery commitments and technical constraints.
• Drive automation and continuous improvement initiatives.
• Revise workflows to integrate AI and new technologies to reduce development cycles.
• Contribute to the long-term evolution of EMS healthcare data products.

Your responsibilities will be

Technical Leadership

• Lead and mentor a team of Data Engineers (currently one person).
• Define, review, and coordinate the team's work and technical priorities.
• Guide architectural decisions and ensure consistency across developments.
• Review code, mentor developers, and promote engineering best practices.
• Ensure technical debt is identified, documented, and addressed appropriately.
• Act as the primary technical escalation point for the Data Engineering domain.

Product Delivery & Backlog Management

• Maintain and continuously refine the operational backlog in Jira.
• Translate product objectives and functional requirements into prioritized technical tasks.
• Work closely with the Product Lead to ensure roadmap objectives are executable.
• Provide effort estimates and technical feasibility assessments.
• Identify dependencies, risks and capacity constraints.
• Ensure developments are delivered according to agreed priorities and commitments.

Quality & Automation

• Define and implement testing strategies and quality-control mechanisms.
• Establish automated product validation and monitoring processes.
• Build automated reporting and alerting systems.
• Improve traceability, reproducibility and reliability of data processes.
• Promote DataOps practices and continuous improvement.
• Design and implement scalable data pipelines and processing workflows.
• Develop algorithms supporting terminology mapping, data normalization and quality assessment.
• Automate terminology ingestion and integration processes.
• Collaborate with Product, Data Science and Engineering teams to deploy production-ready solutions.
• Contribute to the continuous evolution of the Termino platform and related products.

Team & Cross-functional Collaboration

• Support the professional growth and development of team members.
• Foster a culture of ownership, collaboration and continuous learning.
• Participate in capacity planning and delivery planning activities.
• Collaborate closely with Product, Operations, Data Science and commercial stakeholders.
• Provide regular visibility on progress, risks and resource needs.

What Success Looks Like

During your first year, you will:

• Successfully lead and develop the Data Engineering team.
• Establish a clear and main