Data & AI Engineer (Pharma / Life Sciences) 6-12 month Contract
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We are seeking experienced Data & AI Engineers to support enterprise data and analytics initiatives within a leading global pharmaceutical organization. Reporting into the VP of Data & AI, these roles will play a critical part in building and scaling data platforms, enabling advanced analytics, and deploying AI/ML solutions across R&D, manufacturing, and commercial functions.
This is a high-impact contract opportunity to work on cutting-edge data and AI use cases in a regulated, large-scale environment.
Key Responsibilities:
Design, build, and maintain scalable data pipelines to ingest, transform, and integrate data from clinical, manufacturing (MES), laboratory, and commercial systems
Develop and optimize data models and architectures to support analytics, reporting, and machine learning use cases
Collaborate with data scientists and business stakeholders to productionize AI/ML models
Implement real-time and batch data processing solutions in cloud environments (AWS, Azure, or GCP)
Ensure data quality, integrity, and compliance with regulatory standards (GxP, FDA, 21 CFR Part 11)
Integrate data from systems such as DeltaV, Rockwell PharmaSuite, PAS-X, LIMS, and ERP platforms
Support use cases including predictive maintenance, process optimization, clinical trial analytics, and supply chain forecasting
Contribute to data governance, metadata management, and documentation standards
Required Experience:
5+ years of experience in data engineering, analytics engineering, or AI/ML engineering roles
Strong hands-on experience with Python, SQL, and data pipeline frameworks (e.g., Spark, Airflow, Databricks)
Experience working with cloud-based data platforms and modern data architectures (data lakes, lakehouse, streaming)
Familiarity with pharma or life sciences data environments, including clinical, manufacturing, or quality systems
Experience working in regulated environments (GxP) strongly preferred
Ability to xsgimln work cross-functionally with technical and non-technical stakeholders
Preferred Qualifications:
Experience integrating MES, LIMS, or historian data (e.g., OSIsoft PI)
Exposure to AI/ML model deployment (MLOps frameworks, CI/CD pipelines)
Knowledge of data standards such as CDISC, HL7, or OPC
Prior experience working in large enterprise or consulting environments
Engagement Details:
Contract length: 6–12+ months (with potential extensions)
Work environment: Hybrid (Only US based considered)
High-visibility role supporting enterprise-wide digital transformation initiatives
No third parties considered