Engineering Manager (Data)

The Engineering Manager is a key leader within our Technical Implementation organization, leading a globally distributed team of approximately 10–12 data engineering professionals. This role bridges client delivery, technical execution, and people leadership, with a strong focus on successful client implementations and scalable, high-quality data engineering practices.

This hands-on leadership role combines technical depth with operational discipline. The manager will guide feature delivery teams, partner with cross-functional stakeholders, and ensure reliable execution across complex healthcare data use cases, including ETL workflows, data mapping, and clinical data integration.

- Lead Client Implementations: Manage end-to-end client implementations, ensuring timely, high-quality delivery aligned with client expectations.

- Guide Data Engineering Execution: Provide technical leadership across ETL, data mapping, and integration workflows, promoting consistency and best practices.

- Optimize Interoperability Workflows: Work with stakeholders to improve CMS Interoperability and related implementation processes.

- Manage Global Teams: Partner with offshore and distributed teams to coordinate delivery, align priorities, and maintain operational rigor.

- Coach and Develop Talent: Mentor engineers and new hires while building a collaborative, performance-driven team culture.

- Own Operational Execution: Support delivery management, resource planning, and prioritization with delivery and product teams.

- Set and Track Performance Metrics: Define team success measures, monitor progress, and drive continuous improvement.

- Encourage Innovation: Promote practical adoption of tools, technologies, and approaches that improve scalability, quality, and efficiency.

What you bring to the team

- 7+ years of experience in data engineering roles, including client‑facing implementations.

- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

- Demonstrated experience leading and mentoring technical teams.

- Strong hands‑on experience designing and supporting ETL workflows and complex data integrations. Proficiency with Python and PySpark for data processing and transformation.