Lead Data Engineer

About Us:

RELI Group is seeking a Lead Data Engineer to provide technical leadership for the CMS MIDAS modernization initiative. Following the migration to Databricks, MIDAS is entering a critical platform hardening phase focused on standardization, architectural discipline, CI/CD reconstruction, data model unification, and automation of data transformation validation.

This role serves as the technical lead across multiple Scrum teams, guiding a distributed team of Data Engineers and establishing enforceable engineering standards. The Lead Data Engineer is responsible for defining how the work is executed - not just completing individual tasks.

The objective is to engineer a sustainable, scalable lakehouse foundation that prevents operational fragility and enables future optimization, advanced analytics, and AI capabilities.

• Technical Leadership & Vision
• Define and enforce engineering standards across all Databricks development efforts.
• Lead implementation of a formal Bronze / Silver / Gold medallion architecture.
• Drive alignment toward a unified data model across domains.
• Establish code quality, naming conventions, reusable frameworks, and architectural patterns.
• Serve as the technical escalation point for complex data engineering challenges.
• Execution Across Scrum Teams
• Oversee Data Engineers embedded across multiple Scrum teams.
• Provide architectural guidance during backlog refinement, sprint planning, and design sessions.
• Identify cross-team dependencies and proactively remove technical blockers.
• Ensure consistent Definitions of Done that include testing, documentation, and deployment discipline.
• Partner with Release Management and DevOps to align data engineering with deployment workflows.
• CI/CD & Governance Modernization
• Lead reconstruction and enforcement of CI/CD pipelines across lower environments (Dev/Test/Stage).
• Establish test data strategies to support lower-environment validation and automated regression testing.
• Rationalize GitHub repository structure, branching strategy, and version control governance.
• Implement automated data transformation testing frameworks.
• Strengthen observability, lineage, and data quality controls.
• Strategic Platform Stewardship
• Partner with Program Leadership to define phased modernization roadmaps.
• Sequence foundational work prior to optimization and AI enablement initiatives.
• Ensure technical debt is surfaced, prioritized, and reduced methodically.
• Advise leadership on risk tradeoffs between speed and architectural integrity.

• 8+ years of data engineering experience, with demonstrated technical leadership.
• Deep hands-on expertise with Databricks, Delta Lake, PySpark, and lakehouse architecture.
• Experience implementing medallion architectures and unified data models.
• Proven experience leading or mentoring data engineering teams.
• Experience designing or rebuilding CI/CD frameworks for data pipelines.
• Strong Git governance and repository management experience.
• Experience working across multiple Agile/Scrum teams in a scaled delivery model.
• Ability to translate architectural vision into enforceable execution standards.

• Experience stabilizing or restructuring complex inherited analytics platforms.
• Experience supporting CMS or other federal healthcare programs.
• Familiarity with regulated environments (FISMA, ARS 5.0).
• Exposure to AI/ML enablement efforts, with understanding of prerequisite data engineering discipline.

• Data Engineering & Lakehouse Implementation
  Databricks (Notebooks, Workflows, Repos)
  Delta Lake (ACID transactions, versioning, optimization)
  Medallion architecture implementation (Bronze / Silver / Gold layering)
  Large-scale distributed processing with PySpark
• Programming & Data Transformation
  Python
  SQL
  PySpark
  Data transformation frameworks and reusable pipeline design
• CI/CD & Environment Management
  GitHub (branching strategy, pull request governance, repo hygiene)
  CI/CD pipeline design for data engineering workflows
  Promotion models across Dev / Test / Stage / Prod
  Automated regression testing for data pipelines
• Data Quality & Validation
  Test data strategy development (synthetic or masked data)
  Automated data validation frameworks
  Schema enforcement and evolution management
  Data observability and logging best practices
• Cloud Platform
  AWS (S3, IAM, compute management, cost optimization basics)
  Cluster performance tuning and workload scheduling
• Agile Delivery & Scaled Execution
  Working across multiple Scrum teams
  Definition of Done enforcement
  Backlog refinement from a technical standards perspective

EEO Employer:

RELI Group is an Equal Employment Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, citizenship status, military status, protected veteran status, religion, creed, physical or mental disability, medical condition, marital status, sex, sexual orientation, gender, gender identity or expression, age, genetic information, or any other basis protected by law, ordinance, or regulation.

HUBZone:

We encourage all candidates who live in a HUBZone to apply. You can check to see if your address is located in a HUBZone by accessing the SBA HUBZone Map.

The annual salary range for this position is $140,000.00 to $170,000.00. Actual compensation will depend on a range of factors, including but not limited to the individual's skills, experience, qualifications, certifications, location, other business and organizational needs, and applicable employment laws. The estimate displayed represents the typical salary range for this position and is just one component of the total compensation package for employees. RELI Group provides a variety of additional benefits to its employees. For additional details on the benefits that RELI Group offers click here