Data Engineer

Cognizant Life Sciences Manufacturing Group (LSMG) About the Role We’re looking for a Data Analytics Engineer to join our team on site with a leading global pharmaceutical manufacturer. You’ll deliver the Power BI and Tableau reporting that operations, quality assurance, and senior leadership use to run the site. That includes the SQL, data models, and data flows that sit behind it. The role is hands-on and stakeholder-facing, in a GxP-regulated manufacturing environment where data accuracy and integrity are non-negotiable. Responsibilities - Design and deliver executive-level Power BI and Tableau dashboards that surface real-time manufacturing KPIs, batch quality metrics, equipment OEE, and yield analytics. - Build and maintain ETL/ELT pipelines that bring manufacturing data from OSI PI, MES, LIMS, and QMS systems into SQL Server and Oracle data warehouses. - Optimise data models and SQL query structures to improve dashboard load times and keep reporting scalable as data volumes grow. - Integrate process analytics tools, including BIOVIA Discoverant and OSI PI Integrator, to support both real-time and historical analysis across manufacturing lines. - Develop SQL and Python automation for data reconciliation, exception reporting, and batch processing workflows, reducing manual data handling. - Implement GxP-compliant data integrity controls, such as automated validation rules, audit trails, and structured error handling, in line with FDA 21 CFR Part 11 and EMA data integrity guidance. - Set up pipeline monitoring and alerting through automated health checks and threshold-based notifications, so that data quality issues are resolved before they affect manufacturing reporting or regulatory submissions. - Work as the main data liaison between manufacturing engineers, QA leads, and IT architects, turning operational requirements into scalable reporting solutions. - Maintain technical documentation for pipelines, ETL processes, and reporting assets in Confluence to support audit readiness and knowledge transfer. Qualifications - 3+ years’ experience as a data analytics, BI, or data engineer, including delivery in a pharmaceutical manufacturing environment. Required Skills - Strong Power BI and Tableau development skills, with a record of executive dashboards in production use. - Advanced SQL across SQL Server and/or Oracle, including query optimisation and data modelling for reporting performance. - Experience working with manufacturing data sources such as process historians, MES, LIMS, or QMS. - Working knowledge of GxP data integrity requirements, including 21 CFR Part 11 and EMA data integrity expectations. - Confidence working directly with manufacturing, quality, and IT stakeholders on a client site. Preferred Skills - Hands-on experience with OSI PI and PI Integrator. - Experience with BIOVIA Discoverant or similar process analytics tools. - Python for automation, reconciliation, and exception reporting. - Experience designing pipeline monitoring, health checks, and alerting. - Familiarity with Confluence or similar tools for controlled technical documentation.