Data Engineering Manager, Integrations

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineering Manager, Integrations in the United States.

This role provides the opportunity to lead and grow a high-performing data engineering team focused on ingesting, harmonizing, and operationalizing complex healthcare data across multiple products. You will be responsible for scaling client onboarding, enhancing data quality, and ensuring resilient, cost-effective ELT pipelines. Collaborating closely with Product, Clinical, Data Science, and Engineering teams, you will set technical standards, mentor engineers, and drive measurable outcomes that directly impact operational efficiency and client success. This is a fully remote position where you can shape the future of data integrations in a fast-paced, mission-driven environment.

Accountabilities:

• Lead, coach, and develop a team of data and analytics engineers, fostering technical excellence and a collaborative culture.
• Ensure timely delivery of client data integrations by maintaining enterprise data model standards and consistent data definitions.
• Oversee data pipelines using modern tooling (dbt, Airflow, Snowflake, AWS, Python) to ensure reliability, observability, and cost-effectiveness.
• Drive onboarding speed by implementing automation, reusable patterns, and clear runbooks.
• Establish and enforce SLOs/SLAs, implement monitoring, and lead post-incident reviews to improve pipeline resiliency.
• Implement comprehensive data quality and testing frameworks, including schema validation, referential integrity, and lineage observability.
• Collaborate cross-functionally to prioritize roadmaps, manage trade-offs, and deliver measurable outcomes.
• Manage high-volume client integration requests, triaging, prioritizing, and communicating timelines effectively.
• Own daily operations rhythm, including ticket review, resource allocation, and stakeholder updates.
• Track operational metrics to identify bottlenecks and improve client integration outcomes.

• 7+ years of data engineering experience, including leadership of engineers and delivery outcomes.
• Deep experience with healthcare datasets, including clinical and/or billing/claims; familiarity with HL7/FHIR and interoperability patterns.
• Strong SQL and data modeling skills, with proven experience building reliable ELT pipelines in dbt, Airflow, Snowflake, and Python.
• Operational excellence mindset, including SLOs/SLAs, incident management, root-cause analysis, and preventive improvements.
• Proven ability to accelerate client onboarding through automation, standardization, and repeatable patterns.
• Excellent communication and stakeholder management skills, with the ability to align cross-functional teams.
• Hands-on approach and willingness to contribute directly to unblock the team.
• Nice to have: experience at scale-up or rapid-growth companies, leading complex client integrations, certifications in Snowflake, AWS, dbt, or healthcare data, and hands-on interoperability experience (HL7, FHIR, CCD/C-CDA).