Data Architect / Engineer– Azure Fabric & AI Data Platform

Data Architect / Engineer– Azure Fabric & AI Data Platform

Location: Indianapolis, IN 

Final round will be Onsite 

Job Summary:

Seeking a hands-on Data Engineer to build scalable data pipelines, API integrations, AI-powered document ingestion solutions, and cloud-native data platforms using Microsoft Azure Fabric, PostgreSQL, Python, and AWS. The role focuses on structured and unstructured data ingestion, ETL/ELT development, LLM integration, and Medallion Architecture (Bronze/Silver/Gold).

Key Responsibilities

• Build and maintain Azure Fabric data pipelines integrating laboratory, PLM, LIMS, and enterprise systems.
• Develop API connectors, MCP integrations, and AI-driven document ingestion pipelines.
• Implement Bronze, Silver, and Gold data layers with data quality controls and lineage tracking.
• Integrate LLMs and vector search solutions for document retrieval and semantic search.
• Design and optimize PostgreSQL schemas and scalable data models.
• Deploy and support cloud-native solutions across Azure and AWS environments.
• Ensure compliance with data governance, security, and audit requirements.

Mandatory Skills

• Microsoft Azure Fabric (Lakehouse, Data Factory, Pipelines, Delta Lake)
• Python & PySpark
• ETL/ELT Pipeline Development
• Azure Data Factory & Azure Blob Storage
• PostgreSQL & Advanced SQL
• Data Modeling & Medallion Architecture (Bronze/Silver/Gold)
• REST APIs, OAuth, API Integrations
• Azure OpenAI / OpenAI / Claude APIs
• RAG, Vector Databases, Azure AI Search
• Document Ingestion, OCR, Azure Document Intelligence
• AWS (S3, Lambda, Glue, API Gateway, RDS/Aurora)
• Docker, CI/CD, Git
• Data Governance, Data Lineage, Audit Trails
• ALCOA+ / GxP Compliance Knowledge

Required Qualifications

• 5+ years of Data Engineering experience.
• Strong hands-on expertise in Azure Fabric and enterprise data platforms.
• Experience with Python, PySpark, PostgreSQL, ETL/ELT, and API development.
• Proven experience implementing AI/LLM-powered data solutions and RAG architectures.
• Experience with AWS data services and cloud integrations.
• Exposure to regulated environments (Life Sciences, Pharma, Medical Devices) is highly preferred.

Preferred

• Pharma, Biotechnology, or Medical Device domain experience.
• GxP, 21 CFR Part 11, and ALCOA+ knowledge.
• Experience with Teamcenter, LabVantage LIMS, Veeva Vault/QDocs, or Darwin.
• Azure Data Engineer and/or AWS Data Engineer Certification.