Advanced Analytics Engineer Lead

What We Offer

Shape the future of healthcare analytics at Novant Health. As an Advanced Analytics Engineer Lead, you'll design and deliver high-quality, analytics-ready data products within Nucleus, our enterprise data warehouse, enabling data-driven decisions across the organization.

In this lead technical role, you'll lead the development of dimensional data models, curated data marts, and reusable data assets using Databricks Unity Catalog. You'll optimize solutions for Power BI and other analytics platforms, establish engineering best practices, and mentor fellow Analytics Engineers. You'll also ensure data products are secure, reliable, scalable, and trusted by the business.

Schedule: 8:00AM – 5:00PM

Location: Remote

Department: SPX Governance

Key Responsibilities:

• Lead the design and delivery of enterprise data products, including facts, dimensions, aggregates, and data marts.
• Build scalable, high-performing solutions in Databricks and Unity Catalog.
• Optimize data models for Power BI and self-service analytics.
• Establish reusable development standards and engineering best practices.
• Mentor team members and provide technical leadership on complex initiatives.
• Drive data quality, governance, security, documentation, and production reliability.

Why This Role Matters:

Your work will transform complex data into actionable insights that improve patient care, operational performance, and strategic decision-making across Novant Health.

What We're Looking For

• Education:
  • 4 Year / Bachelors Degree, required.
  • Bachelor’s degree in computer science or information systems required. In lieu of a bachelor’s degree, four (4) years of additional relevant experience, beyond the minimum experience requirement, will be considered.
  • Graduate Degree, preferred. Master’s Degree Preferred master’s degree in computer science or information systems.
• Experience:
  • 7 Required Minimum seven years of analytics engineering, data engineering, data warehousing, analytics development, and/or business intelligence experience.
• Additional Skills (required):
  • Advanced proficiency in SQL, Python, PySpark, Spark SQL, Delta Lake, and Databricks for large-scale data transformation and analytics engineering.
  • Advanced expertise in dimensional modeling, including facts, dimensions, conformed and role-playing dimensions, bridges, outriggers, aggregates, surrogate keys, slowly changing dimensions, and data grain.
  • Experience developing curated data marts and reusable analytics assets using medallion architecture patterns.
  • Experience building modular, maintainable, metadata-driven transformation code and reusable Nucleus framework components for batch and incremental processing.
  • Experience with orchestration and scheduling technologies such as Apache Airflow, Databricks Workflows, or similar tools, including dependency management, exception handling, restartability, and monitoring.
  • Experience with Azure DevOps, Git, pull requests, code review, CI/CD, automated deployment, and environment promotion across development, UAT, and production.
  • Advanced understanding of data quality engineering, including unit testing, reconciliation, referential-integrity validation, completeness checks, regression testing, and automated data-quality rules.
  • Experience optimizing Databricks and Spark workloads for performance, scalability, reliability, and efficient incremental processing.
  • Experience applying Databricks Unity Catalog, lineage, metadata, classification, auditing, and secure access patterns to governed data products.
  • Understanding of row-level filtering, column masking, least privilege, PHI/PII protection, and healthcare privacy and security requirements.
  • Ability to translate complex clinical, operational, and financial requirements into scalable models, transformation rules, acceptance criteria, and implementation plans.
  • Ability to lead root-cause analysis and resolve complex production, data-quality, performance, schema, and downstream-consumption issues.
  • Strong documentation, facilitation, mentoring, problem-solving, and communication skills.
• Additional Skills (preferred):
  • Experience with Epic source data, including Clarity and Caboodle, and understanding of healthcare workflows and data domains.
  • Experience designing Nucleus data products that support enterprise and composite Power BI semantic models using DirectQuery.
  • Experience with Delta Live Tables, Delta Sharing, APIs, event or streaming technologies, and Azure Data Lake Storage.
  • Experience implementing data contracts, metadata-driven frameworks, observability, automated lineage, and data-quality scorecards.
  • Experience with healthcare interoperability formats and standards such as HL7, FHIR, CCDA, JSON, XML, and Parquet.
  • Working knowledge of Power BI semantic modeling, DAX behavior, query folding, model relationships, and DirectQuery performance
  • Experience with dbt or comparable analytics engineering transformation and testing frameworks.