Analytics Engineer

Hearst•Charlotte, NC

About The Position

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.

Requirements

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.
DevOps: Familiarity with Git, CI/CD, and modern development workflows.
Communication: Proven ability to collaborate with stakeholders and escalate data requirements or constraints effectively.

Nice To Haves

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.

Responsibilities

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.