Senior Technical Specialist

Good to have: Experience in life sciences, pharma, crop science or regulated enterprise environments.Job SummaryRequired experience: approximately 12-16 years of relevant engineering experience. The Data Engineer - Proficient will design and build scalable data pipelines, data models and analytics-ready data products for Bayer platforms. The role supports AI readiness, reporting, governance and data product enablement across squads.Key ResponsibilitiesBuild and optimize batch / streaming data pipelines, transformations and data integration workflows.Develop data models, data quality checks, data validation routines and analytics-ready datasets.Work with cloud data platforms, lakehouse / warehouse technologies and BI / visualization tools.Support data lineage, metadata, governance, access controls and documentation.Collaborate with AI Engineers and Data Scientists to prepare AI-ready datasets.Participate in sprint ceremonies, design reviews, data quality reviews and production support activities.Use engineering practices such as Git, CI/CD, testing and automated validation for data pipelines.Skill RequirementsStrong hands-on experience in Python, SQL and data engineering practices.Experience with AWS / Azure, Snowflake, Databricks and modern data platform capabilities.Knowledge of ETL / ELT, data modelling, data quality, metadata and data governance.Experience with PowerBI / Tableau or equivalent BI / reporting platforms.Ability to implement automated data validation, monitoring and pipeline reliability practices.Other RequirementsStrong understanding of privacy, compliance and enterprise data governance.Ability to work with business, platform, analytics and AI teams.Good to have: Agentic AI experience, data validation agents, data product assistants, AI-assisted data pipeline generation, metadata agents or AI-enabled data governance workflows.Good to have: Experience in life sciences, pharma, crop science or regulated enterprise environments.