Cognizant Life Sciences Manufacturing
Data Analytics & AI Engineer,
Builds and maintains batch and streaming data pipelines on Azure Databricks/AWS and delivers Power BI analytics for life-sciences manufacturing, while designing and productionizing agentic AI/LLM solutions (RAG, tool calling, multi-step workflows) with manufacturing, quality and engineering teams under GMP data-integrity expectations.
- Compensation
- Not disclosed
- Location
- Cork, Ireland
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data analytics
- Posted
Skills
Must have
- Degree in Computer Science, Engineering, Data Science or similar (or equivalent experience)
- Hands-on experience with Azure Databricks or a similar Spark platform
- Experience building analytics solutions that stakeholders use for decisions
- Practical experience building AI solutions with agents and/or LLMs
- Strong Python and SQL
- Delta Lake, Airflow/Databricks Workflows and Git-based CI/CD
- Self-starter who communicates clearly with non-technical stakeholders
Nice to have
- GMP or other regulated-industry experience (manufacturing, pharma, life sciences)
- AWS/GCP
- MLOps/LLMOps or vector databases
- Data governance or cataloguing exposure
Full description
Data Analytics & AI Engineer, Manufacturing Data & AI
About the role
Join our Manufacturing Data & AI team and help turn manufacturing data into decisions. You’ll build reliable data pipelines, deliver Power BI analytics, and design AI agent and LLM solutions that solve real manufacturing problems, working directly with manufacturing, quality and engineering teams from problem framing through to delivery.
What you’ll do
- Build and maintain scalable batch and streaming pipelines on Azure Databricks/AWS, with data quality checks, monitoring and CI/CD
- Deliver dashboards, semantic layers and self-service data products that answer real business questions
- Design and productionize agentic AI and LLM applications (RAG, tool calling, multi-step workflows) integrated with enterprise data and systems
- Drive projects independently from requirements to deployment, working within GMP expectations for data integrity and traceability
What you’ll bring
- Degree in Computer Science, Engineering, Data Science or similar (or equivalent experience)
- Hands-on experience with Azure Databricks or a similar Spark platform
- Experience building analytics solutions that stakeholders use for decisions
- Practical experience building AI solutions with agents and/or LLMs
- Strong Python and SQL, plus Delta Lake, Airflow/Databricks Workflows and Git-based CI/CD
- A self-starter who communicates clearly with non-technical stakeholders
Nice to have
- GMP or other regulated-industry experience (manufacturing, pharma, life sciences)
- AWS/GCP, MLOps/LLMOps or vector databases
- Data governance or cataloguing exposure