Data Engineer (BI)

Key Responsibilities

• Design and maintain semantic data models, metrics layers, and certified datasets that provide a consistent, business-friendly source of truth for reporting and self-service analytics.
• Define, standardize, and govern KPIs, calculation logic, and a shared metric glossary so that metrics are consistent and trusted across dashboards and self-service analytics.
• Develop, maintain, and optimize dashboards and reports in Sigma (primary), with some Power BI and native Databricks dashboards/AI-Bi Genie, and enable business users to explore data through governed self-service analytics.
• Define and maintain Sigma workspace standards (workbook templates, certified datasets, RLS configuration, naming/governance conventions) in the development instance for promotion across tenant environments, in partnership with Platform Engineering, for tenant-level administration.
• Collaborate with the Architecture team on data quality, testing, and observability; own triage and resolution of BI-layer/dashboard issues.
• Drive BI adoption by training and supporting business users, monitoring dashboard usage, and identifying underused or redundant assets for redesign, training, or deprecation.
• Ensure data security and compliance, including role-based access controls for security, encryption, masking, and governance best practices to ensure compliant handling of sensitive information.
• Gather reporting and analytics requirements from business stakeholders, define success measures, and translate them into technical specifications and well-structured data products.
• Enable analytics, reporting, and AI/ML use cases through well-structured, business-friendly data models, feature availability, and platform integrations using tools such as Databricks Vector Search and Model Serving.
• Collaborate within an Agile-Scrum framework and develop comprehensive technical design documentation to ensure efficient and successful delivery.
• Build and maintain production dashboards and workbooks in Sigma, ensuring reliability and performance for business users.
• Implement row-level security and Entra ID-based access controls to govern and secure data access within the BI/data platform.
• Collaborate and communicate proactively with engineering, analytics, and business stakeholders, influencing priorities and driving alignment across teams.

Requirements

• 3+ years of hands-on data engineering and/or business intelligence experience required.
• Experience in Databricks, including DAB and Materialized Views, required.
• 3+ years designing semantic/dimensional data models and building dashboards and reports in a modern BI platform including hands-on experience with a metrics or semantic layer required.
• 3+ years of experience with analytical SQL (ANSI SQL/T-SQL/Spark SQL) and Python for data engineering, including pipeline construction, transformation logic, and automation required.
• Azure DevOps; GitHub CoPilot knowledge is a plus.
• Bachelor's degree in Computer Science, Information Technology, or a related field. Master's degree preferred.
• Experience dealing with HIPAA compliant data sets is a plus.