Azure Data Engineer- Payer_Remote Work

Azure Data engineer- Payer Location: Remote work Duration: 12 Months + U.S. Work Authorization required (No sponsorship available). W2 candidates only. No C2C or sub-vendor submissions. Senior, hands‑on data engineering contractor to support Modern data platform delivery across Health Payer Domains. This role requires independent ownership of end‑to‑end data pipelines using modern cloud and Lakehouse architecture. This is a hit‑the‑ground‑running role with minimal ramp‑up. 1. Key Responsibilities • Design, build, and operate end‑to‑end data pipelines • Source ingestion → transformation → analytics‑ready datasets • Develop transformations and data models using SQL and Python • Implement automated data quality checks and validations • Follow Git‑based development • Collaborate with business/domain stakeholders on data rules and definitions • Ensure solutions are secure, auditable, reliable, and supportable • Produce clear technical documentation and operational notes 1. Required Technologies (Must‑Have) Candidates must have strong, recent hands‑on experience with most of the following: Languages • SQL • Python (PySpark preferred) Data Platforms / Storage • Cloud data platforms (Azure preferred; AWS/GCP acceptable) • Azure Data Lake Storage Gen2 (ADLS Gen2) or equivalent • Object storage–based data lakes • Parquet format • Lakehouse concepts (Iceberg and/or Delta) Transformation & Modeling • dbt (dbt Core and/or dbt Cloud) Source Control, GitOps & CI/CD • GitHub • Pull request–based development • CI/CD pipelines (GitHub Actions or equivalent) Compute (one or more) • Snowflake • Microsoft Fabric • Databricks 1. Preferred / Nice‑to‑Have Technologies • Microsoft Fabric Data Factory / Azure Data Factory • Fabric or Databricks Notebooks • Orchestration tools (Airflow, Dagster, or similar) • Healthcare / payer domain experience (Clinical, Claims, Provider) 1. Required Experience • 7+ years of hands‑on data engineering experience • Proven delivery of production‑grade data pipelines • Experience working independently with minimal supervision • Strong understanding of data quality, reliability, and operational readiness 1. Ideal Candidate Profile • Senior, hands‑on data engineer • Engineering generalist (not tool‑only or reporting‑only) • Comfortable working in ambiguous, fast‑moving environments • Strong delivery and ownership mindset 1. Recruiter / Vendor Screening Notes • Not an entry‑level role • Not a BI‑only or reporting‑focused role • Candidates must demonstrate end‑to‑end pipeline ownership • Hybrid role — candidates must be open to periodic on‑site presence