Analytics Engineer

Hearst Television (HTV) 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.

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

• Experience:
  
  7+ years in business analytics, data modeling, or data engineering (or a Master’s degree with 5+ years of experience).
• Modeling Expertise: 5+ years of deep experience with relational modeling concepts and Microsoft tabular semantic models.
• Technical Proficiency:
  Expert-level SQL skills and 5+ years of experience with Power BI, DAX, and Spark (Spark SQL/PySpark/Scala).
• Platform Knowledge:
  Strong hands‑on experience with Microsoft Fabric tools and the Delta Lake format.
• Logic & Design:
  Demonstrated experience translating complex business requirements into technical requirements using Star Schema/Dimensional modeling.
• Dev Ops:
  Familiarity with Git, CI/CD, and modern development workflows.
• Communication:
  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.

At Hearst Television we tell stories every day. Stories about people of all backgrounds, perspectives, and identities. That’s why, behind the scenes, we believe in being an organization that fosters collaboration and open communication, ensuring that the content we create is authentic, accurate, and connected to the communities we serve.

Hearst's benefit programs are modern, flexible and designed to focus on you. As a Hearst employee, you and your spouse or partner or dependents would have access to the following benefits:

• 401(k) matching
• Emotional Wellness Support

Hearst Television (HTV) owns and/or operates 35 television and two radio stations serving 27 media markets across 39 states reaching over 22 million U.S. television households. HTV is recognized as one of the industry's premier broadcasting companies and has been honored with numerous awards for distinguished journalism, industry innovation, and community service.

We are an Equal Opportunity Employer. we do not discriminate in hiring on the basis of sex, gender identity, sexual orientation, race, color, religion, creed, national, origin, physical or mental disability, protected veteran status, or any other characteristic protected by federal, state, or local law.