Data Engineer Senior

A cover letter is required for consideration and should be attached as the first page of your resume. The cover letter should describe your specific interest in the position and highlight skills and experience that directly relate to this role.

Join the Pharmacy Data Solutions team at Michigan Medicine as a Data Architect Senior, where you will serve as a hands-on technical builder supporting the pharmacy analytics platform across operational, financial, and clinical domains.

This role is responsible for building, maintaining, and improving the data products and workflows that support pharmacy reporting, dashboarding, and analytics delivery. The work spans data modeling, pipeline development, production troubleshooting, validation, and reporting support across a wide range of pharmacy use cases.

This is a hands-on technical role operating within a small, high-autonomy team. The Data Architect Senior is expected to move fluidly across backend engineering work, analytics enablement, and occasional dashboard/reporting support as needed to meet team and departmental priorities.

The successful candidate will be comfortable shifting between SQL/dbt model development, Python-based workflow support, issue triage, metric validation, and collaboration with analysts and business stakeholders to deliver reliable data solutions.

This position reports to the Director of Pharmacy Analytics.

Data Engineering, Modeling & Delivery

• Build, maintain, and improve data models using dbt and modern analytics engineering practices.
• Develop and support ETL/ELT workflows integrating financial, operational, clinical, and other pharmacy data sources.
• Write and maintain Python-based data workflows and support orchestration in tools such as Prefect or similar platforms.
• Troubleshoot production issues, investigate data discrepancies, and resolve failures in pipelines, models, and downstream reporting.
• Support data validation, QA, and reconciliation efforts to improve reliability and trust in analytics outputs.
• Continuously improve data pipeline performance, operational reliability, and maintainability.

Reporting, Analytics Support & Small-Team Flexibility

• Support dashboard and reporting delivery when needed, including validation of data sources, metric logic, and occasional Tableau-facing work.
• Partner with analysts and stakeholders to clarify business requirements, refine requests, and translate them into practical technical solutions.
• Contribute to ad hoc reporting, data pulls, and analytics support when priorities require it.
• Work across backend engineering, reporting support, and operational delivery in a way that reflects the needs of a small, high-autonomy team.
• Help the team deliver quickly and pragmatically across a broad queue of production, reporting, and strategic work.

Documentation, Standards & Continuous Improvement

• Maintain clear documentation covering workflows, models, validation logic, and operational runbooks.
• Follow and help strengthen standards for naming, testing, maintainability, and version-controlled delivery.
• Identify opportunities to reduce technical debt, simplify workflows, and improve development efficiency.
• Use Git-based workflows and CI/CD practices to support reliable, peer-reviewed delivery.
• Promote practical use of automation and AI-assisted development tools where appropriate.

Collaboration & Technical Contribution

• Contribute directly to implementation work across the analytics lifecycle, including data modeling, pipeline support, QA, and troubleshooting.
• Collaborate closely with analysts, pharmacy leadership, and operational stakeholders to support delivery of reliable reporting and analytics solutions.
• Participate in technical problem-solving and help balance backend platform work with broader team needs.
• Contribute ideas for process improvement, simplification, and better cross-team coordination.

Education

• Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field.
• Master's degree in a relevant field preferred.

Experience

• 3-5 years of professional experience in data architecture, data engineering, analytics engineering, or enterprise data warehousing.
• Demonstrated experience designing and implementing scalable relational database and data warehouse solutions.

Strong proficiency in:

• SQL across major relational database platforms (SQL Server, PostgreSQL, Oracle, or similar).
• Python for data pipeline development and automation.
• dbt or similar analytics engineering frameworks, including dimensional modeling (star/snowflake schemas); dbt preferred.
• Workflow orchestration tools (Prefect, Dagster, Airflow, or similar); Prefect preferred.
• Git-based version control and CI/CD workflows; GitLab preferred.

Additional requirements:

• Experience working with Epic Clarity data models; certification required. Candidates without current certification must obtain it within six months of hire.
• Strong analytical and problem-solving skills with the ability to independently drive technical solutions.
• Strong communication skills, including the ability to translate technical concepts for non-technical stakeholders in a small-team environment.
• Ability to work flexibly across technical delivery, issue triage, and analytics support needs.

Preferred qualifications:

• Experience with BI and visualization tools such as Tableau or Power BI.
• Experience supporting dashboard/reporting delivery, including troubleshooting, validation, and metric review.
• Comfort working in a small team where responsibilities may span backend engineering, reporting support, and stakeholder-facing delivery.
• Healthcare or pharmacy domain experience, including supply chain, medication utilization, reimbursement, or 340B program data.
• Familiarity with healthcare data standards (HL7, FHIR, RxNorm, NDC, NCPDP).
• Experience documenting technical workflows, data models, and operational processes for mixed technical/non-technical audiences.
• Experience mentoring analysts or technical teammates and contributing to shared standards.
• Enthusiasm for AI-assisted development tools and a drive to leverage them for productivity gains.

This position follows a hybrid work schedule, requiring a minimum of one day per week on-site, with option to work remotely from home the other days.

This position may be underfilled at a lower classification depending on the qualifications of the selected candidate.