Data & AI Engineer (Pharma / Life Sciences)

Data & AI Engineer (Pharma / Life Sciences) 6-12 month Contract 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 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