Lead Data EngineerPosition SummaryWe are seeking a Lead Data Engineer to own one or more domains of the data platform,
set their long-term technical direction, and manage a team of senior and mid-level data
engineers. This position plays a key role in supporting the Data Engineering department and
reports to the Manager, Data Engineering, ensuring alignment with organizational goals,
operational excellence, and compliance standards.
Key Responsibilities- Own one or more domains of the data platform on a continuing basis. The initial assignment is expected to be ingestion and orchestration, including the transition off the current managed ingestion platform, replacement connectors, scheduling, and theinterface between raw data and the dbt layer. Other potential domains include the transformation layer and client-facing data feeds.
- Set technical direction for assigned domains, including source onboarding, incremental modeling standards, and decisions on when to rebuild existing pipelines. Document designs prior to development and serve as the final reviewer for domain work.
- Develop and maintain a 12 to 18 month roadmap for each assigned domain, subject to approval by Data & Analytics leadership.
- Establish engineering standards and code review practices for assigned domains for adoption across the Data Engineering team.
- Manage the domain backlog, set priorities, and allocate team capacity across stakeholder requests.
- Ensure the accuracy and timeliness of scheduled client data feeds to manufacturers by building and maintaining testing, monitoring, and reconciliation processes.
- Track and report domain performance to Data, Analytics & AI leadership, including feed timeliness, data accuracy, incident volume, and operating cost.
- Lead incident response for assigned domains, including escalation, post-incident reviews, and corrective actions.
- Design and implement a data quality framework for assigned domains, which includes validation rules, automated testing, monitoring & alerting, and report data quality metrics to stakeholders.
- Design and maintain data access controls that meet HIPAA and BAA requirements including masking policies and role-based access.
- Manage two to three senior and mid-level data engineers, with responsibility for hiring, onboarding, goal setting, performance reviews, compensation recommendations, and performance management. Approximately 65% of time is expected to be hands-on technical work.
- Develop budget recommendations for domain tooling and infrastructure, such as ingestion connectors and Snowflake compute. Lead vendor evaluations (e.g., replacement of the current managed ingestion platform) and present recommendations to the Director, Data, Analytics & AI for approval.
- Serve as the primary point of contact for assigned domains with product, engineering, pharmacy operations, compliance, and account management teams.
- Contribute to the entity-resolution layer that matches patient and provider identities across a variety of source systems.
Qualifications- Education: Bachelor's degree (BA/BS) in Computer Science, Data Science, Information Systems, Software Engineering, Mathematics, Statistics, or a related field, or comparable work experience.
- Licensure/Certification: Not applicable to this role.
- Experience: 7 to 10 years of data engineering experience, including production ownership of a cloud data warehouse (Snowflake preferred) and at least one year of direct people management experience.
Knowledge, Skills, and Abilities:Required:- Production ownership of a cloud data warehouse; Snowflake experience preferred.
- Expert-level SQL and proficiency in Python, including the ability to troubleshoot complex SQL and dbt models.
- Experience with dbt at scale, including incremental models, testing, CI, and project structure.
- Production experience with an orchestration tool such as Airflow, Dagster, or Prefect.
- Experience owning a platform area or major system over multiple years including setting its direction and accountability for results.
- At least one year of direct people management experience, including hiring, performance reviews, and developing engineers at multiple levels.
- Experience implementing automated data quality testing and alerting.
- Ability to communicate data issues, business impact, and resolution timelines to client-facing teams.
- Working knowledge of healthcare data, PHI, and HIPAA requirements.
- Demonstrated ability to lead a team and set technical direction for a domain.
- Experience developing technical roadmaps and making build-versus-buy and vendor recommendations supported by cost analysis.
- Strong leadership, communication, and decision-making skills.
Preferred:- Experience with healthcare, pharmacy, or other regulated data, including PHI, HIPAA, and BAAs.
- Experience with large-scale data platform migrations.
- Experience with infrastructure as code, particularly Terraform.
- Experience with identity resolution or master data management.
- Experience building custom ingestion connectors.
- Familiarity with Looker and LookML. Looker is the primary BI platform at Gifthealth, with Metabase also in use and Domo being retired.
Work Environment- Location: Columbus, OH or remote (US).
- Schedule: Full-time.
- On-call availability may be required to support scheduled client data feeds.
- Regular meetings with the Data Engineering team, direct reports, and Data, Analytics & AI leadership.
Key Essential Functions- Not applicable. This is a standard office/remote engineering role with no physical labor requirements.
- Periodic on-site visits to the Columbus distribution center and call center are expected, primarily during onboarding.
Employment ClassificationStatus: Full-time
FLSA: Exempt
Salary Description
$150,000-170,000
