Azure Data Engineer

Hearst Television•Charlotte, NC

About The Position

Hearst Television (HTV) is hiring an Azure Data Engineer to lead the build of our next-generation data platform. You will be instrumental in migrating our data infrastructure from legacy system to a cutting-edge Microsoft Fabric ecosystem. You will design the Medallion architecture, ensuring a seamless, scalable data flow from diverse source systems into our OneLake environment. This role is central to our mission of owning our data future and driving innovation in media sales.

Requirements

Experience: 5–7 years as a Data Engineer in an enterprise environment with a proven track record in Azure Cloud.
Cloud Architecture: Deep proficiency in Azure-native components, including Azure Data Lake Gen2, API Gateway, and Microsoft Fabric.
Coding & Scripting: Expert-level Python (including API development with FastAPI) and SQL across relational and NoSQL databases.
Big Data Tools: Strong hands-on experience with Spark (PySpark) and Delta Lake principles.
Automation: Demonstrated experience with serverless compute (Azure Functions) and YAML-based CI/CD workflows.
Certification: Microsoft Certified: Azure Data Engineer Associate is strongly preferred.
Soft Skills: Ability to lead architectural discussions and navigate complex cloud environments (Subscriptions, VNETs, Managed Identities).

Responsibilities

Pipeline Orchestration: Design, build, and deploy complex ETL/ELT pipelines using Azure Data Factory and Fabric Data Pipelines to power our enterprise analytics.
Compute & Automation: Develop custom Azure Functions (Python) and API integrations to bridge gaps where native connectors are insufficient, ensuring no data source is out of reach.
Hybrid Ingestion: Architect robust ingestion frameworks capable of handling high-velocity real-time APIs and structured scheduled landings (CSV/Parquet).
Storage Optimization: Manage and optimize OneLake/Delta Lake storage to ensure peak performance for downstream Analytics Engineering and AI consumption.
CI/CD & DevOps: Maintain and enhance GitHub Action pipelines to automate deployments across Dev, Test, and Prod environments, ensuring a stable and reliable release cycle.
Governance & Security: Implement best-class data governance, privacy, and security practices, utilizing Managed Identities and VNETs to protect our data assets.
Technical Troubleshooting: Perform root cause analysis on pipeline failures and implement automated monitoring to minimize downtime and points of failure.