Analytics Engineer

Our client is hiring an Analytics Engineer

The ideal candidate will act as the vital bridge between raw data and executive insights. You will take "Bronze" data and transform it into high-value Silver (Cleansed) and Gold (Aggregated) layers.

Your primary goal is to codify complex media sales logic such as Revenue Pacing, Share of Wallet, and Yield into high-performance Semantic Models that power our Power BI dashboards and AI Data Agents.

This role ensures our data is not just accessible, but actionable and intelligent.

• Use Spark and SQL to architect the Silver and Gold layers of our Lakehouse, ensuring all data is rigorously tested, clean, and documented.
• Design and maintain the Microsoft Fabric Semantic Model (Direct Lake mode) to provide a "Single Source of Truth" across the entire organization.
• Partner closely with Sales and Finance stakeholders to translate "What" and "Why" business questions into precise technical data definitions.
• Structure data specifically for LLM consumption, enabling our AI Data Agents to accurately navigate complex hierarchies of stations, advertisers, and categories.
• Implement Row-Level Security (RLS) and maintain data lineage to ensure compliance with Hearst’s unified data strategy.
• Lead the design of project-specific data models, prepare design specifications, and conduct feature estimations in collaboration with cross-functional teams.
• Perform root cause analysis on anomalies and implement solutions to minimize points of failure and optimize data pipeline performance.

• 7+ years in business analytics, data modeling, or data engineering (or a Master’s degree with 5+ years of experience).
• 5+ years of deep experience with relational modeling concepts and Microsoft tabular semantic models.
• Expert-level SQL skills and 5+ years of experience with Power BI, DAX, and Spark (Spark SQL/PySpark/Scala).
• Strong hands-on experience with Microsoft Fabric tools and the Delta Lake format.
• Demonstrates experience translating complex business requirements into technical requirements using Star Schema/Dimensional modeling.
• Familiarity with Git, CI/CD, and modern development workflows.
• Proven ability to collaborate with stakeholders and elevate data requirements or constraints effectively.

• Familiarity with governance, security best practices, and performance tuning in a cloud environment.
• Experience in the media or broadcasting industry is a plus.
• Knowledge of serverless architectures and containerized deployment.