Role Summary
The Engineer - Automation Engineering β Control System Data Analyst is a technical individual contributor on the Foundry Automation Engineering Team. This role provides data engineering and analytics solutions to support data historization and analytics for automation control systems, and contributes to daily operations, reliability, and compliance of control applications and systems used in manufacturing at the Lilly Medicines Foundry. The position collaborates across functional disciplines to support the process control technical agenda, business plan priorities, and compliance objectives.
Responsibilities
- Provide/input to design decisions regarding development and integration of Automation Data Analytics systems and Foundry data analytics initiatives
- Lead development and implementation of analytics strategies and tools for metrics, visualization, and dashboards across multiple platforms
- Interface with Automation teams and user groups to develop requirements and designs meeting business needs
- Promote data analytics usage to support site business goals and train teams on data analytics tools and techniques
- Support qualification and delivery of Automation Servers, Network, Infrastructure, and applications
- Support the Process Control Validation Plan, CSV, Quality Documents, SOPs and related activities
Qualifications
- Required: Minimum B.S. in IT, Engineering or related discipline and 3+ yearsβ experience in Computerized System Validation and Data Analytics, preferably in pharmaceutical manufacturing
- Preferred: 3+ years in Biopharma engineering, operations, or manufacturing; knowledge of GMP regulatory requirements, computer system validation, execution, and data integrity; experience with SCADA, DCS, MES, LIMS, Power BI, QMS, and Site Historian systems; data analysis and contextualization to support site functions and metrics; ability to work in a matrix organization; ability to network with partners; experience for internal Lilly employees (LRL/PRD) preferred
Skills
- Data analytics, data architecture, and data integrity for automation systems
- SQL, PowerBI, and software development applications
- Knowledge of process control systems (DCS, SCADA, BMS, MES, Historian) and data historians (DeltaV, FT Historian, Metasys, Aveva PI, Ignition, WIN911)
- Regulatory compliance (GAMP, 21 CFR Part 11, Data Integrity) and CSV principles
- Automation servers, networks, and infrastructure qualification; visualization and dashboards
- Cross-functional collaboration and effective communication within a matrix organization
Education
- Minimum B.S. in IT, Engineering or related discipline