Data Engineer with ETL/ELT pipelines and API integrations
dhanutek
Position Title: Data Engineer with ETL/ELT pipelines and API integrations Location: Indianapolis,IN (onsite 5 days per week) Duration: T hrough December 2026, possible extension into 2027
Job Description
Pharmaceutical's client is building a governed data and AI platform, integrating device, laboratory, partner, and document data into a unified foundation that supportsregulatoryreporting, advanced analytics, and AI-driven scientificinsights.The Data Engineer is a hands-on builder responsible for developing data pipelines, API integrations, and AI infrastructure that bring structured and unstructured data into a governedAzure- basedarchitecture. This delivery-focused rolerequires designing, coding, testing, and maintaining production-ready solutions across both AI document ingestion and structured ETL/ELT data engineering tracks. This role integrates structured and unstructureddata fromlaboratory systems, product lifecycleapplications, and manufacturing partners into a governed Azure-based data platform, creating a scalable, audit-ready digital thread that supports analytics, AI, and regulatory compliance. Key Responsibilities:
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Design, build, and maintain production ETL/ELT pipelines integrating laboratory and operational systems (e.g., Darwin, Teamcenter/PLM, LabVantage LIMS, Jama, TurboAC, and Qdocs/Veeva) into Microsoft AzureFabric Lakehouse and PostgreSQL.
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Develop and optimize Bronze, Silver, and Gold medallion architecture, including schema mapping, data modeling, referential integrity, and performance optimization.
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Build scalable API integrations and cross-cloud data pipelines across Azure and AWS to support enterprise data integration.
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Implement automated data quality controls, controlled vocabulary normalization, schema validation, Q-gate/specification checks, data lineage, and audit trails to ensure GxP compliance.
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Monitor, troubleshoot, and optimize pipeline performance, reliability, error handling, and operational monitoring in production environments.
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Collaborate with business, engineering, and IT teams to integrate data sources and establish a governed, scalable digital thread supporting analytics, AI, and regulatory reporting.
Required Skills:
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8+ years of hands-on Data Engineering experience building production ETL/ELT pipelines and API integrations.
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Expert-level Python and/or PySpark for data ingestion, transformation, orchestration, testing, and CI/CD.
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Experience with Microsoft Azure Fabric (Lakehouse, Data Factory, Fabric Pipelines, Delta Lake) delivering end-to-end production solutions.
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Hands-on AWS experience, including S3, Glue (or equivalent), and RDS/Aurora.
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Strong SQL and PostgreSQL experience, including normalized schema design, query optimization, indexing, and performance tuning.
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Experience with data modeling, medallion architecture, and Lakehouse design patterns.
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Experience implementing data lineage, quality controls, schema validation, error handling, and monitoring in regulated environments.
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Knowledge of GxP, GMP, GCP within pharmaceutical, biotechnology, or medical device environments
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SCM, WMS, PLM, MM, QA, any validated applications with in a FDA Regulated systems
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