Description

Design and drive enterprise-scale data engineering architectures on Azure Databricks and cloud platforms, defining end-to-end data solutions and engineering standards.

This role is hybrid.

Responsibilities

• Define and implement end-to-end data architecture, including scalable Lakehouse designs using Databricks and Delta Lake.
• Architect enterprise data across domains (Claims, Member, Provider, Eligibility), ensuring consistency and interoperability.
• Establish data governance frameworks, including lineage, quality, metadata, RBAC, and compliance with HIPAA/HITRUST.
• Guide engineering teams on Spark optimization, Delta Lake design, and CI/CD/DataOps/MLOps standardization.
• Lead architecture reviews and translate business requirements into scalable technical solutions.

Required Skills

• 10+ years of experience in data architecture and engineering.
• Deep expertise in Azure Databricks, PySpark, and Delta Lake.
• Strong background in Cloud Architecture, specifically Azure (ADF, ADLS, Synapse).
• Proficiency in Data Modeling (OLTP, OLAP, Dimensional) and Lakehouse patterns.
• Hands-on experience with ETL/ELT pipelines and orchestration frameworks.
• Familiarity with CI/CD and DevOps practices using Azure DevOps and Git.
• Knowledge of metadata and governance tools such as Unity Catalog or Purview.
• Any Graduate degree.

Preferred Skills

• Experience with AI/ML data architectures, feature stores, or multi-cloud environments (Azure + GCP/Snowflake).
• Familiarity with US Healthcare ecosystems, including FHIR/HL7 models and Payment Integrity use cases.

Key Skills

Education

Any Graduate