Analytics Engineer

RedStream Technology; Charlotte (NC); On-site; USD 120,000 - 170,000; Full time

Job summary

RedStream Technology is hiring an Analytics Engineer to bridge raw data and executive insights, transforming Bronze data into Silver and Gold layers for high-value dashboards and AI agents.

You will design semantic models, implement RLS, and collaborate with Sales and Finance to translate business questions into precise data definitions, ensuring data is accessible and actionable.

Qualifications

• 7+ years in analytics, data modeling, or data engineering.
• 5+ years with relational modeling and Microsoft tabular semantic models.
• Expert SQL skills and 5+ years Power BI, DAX, and Spark experience.
• Strong experience with Microsoft Fabric tools and Delta Lake.
• Experience translating business requirements into technical definitions.
• Familiarity with Git, CI/CD, and modern development workflows.
• Collaborate with stakeholders to elevate data requirements.

Responsibilities

• Use Spark and SQL to architect Silver and Gold data layers in a Lakehouse.
• Design and maintain the Microsoft Fabric Semantic Model (Direct Lake).
• Translate business questions into precise data definitions with stakeholders.
• Structure data for LLM consumption for AI Data Agents.
• Implement Row-Level Security and maintain data lineage.
• Lead data model design, specs, and feature estimations with teams.
• Perform root cause analysis on data anomalies and optimize pipelines.

Skills

Analytics engineering

Data modeling

Data engineering

SQL

Power BI

Spark

DAX

Semantic models

Education

Master's degree

Tools

Microsoft Fabric

Delta Lake

Git

CI/CD

Spark SQL

Job description

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.

Responsibilities

• 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.

Requirements

• 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.

Preferred Qualifications

• 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.