Data Engineer

About the role

As a Data Engineer, you are developing and operating reliable data pipelines that enable timely access to high-quality data assets. You are part of a dynamic team of technical experts, working hand-in-hand with subject matter experts, data product managers, semantic experts and data scientists to create data products that help Bayer to accelerate time-to-market, drive innovation and enhance efficiency across the whole pharma value chain.

What you'll do

• Apply cloud and big-data engineering skills to build, test, and maintain data pipelines and data-product components using tools such as Spark, dbt, Airflow
• Execute ingestion, transformation, and loading jobs that reliably move data from operational systems, IoT devices, or clinical sources into data platforms at agreed SLAs
• Troubleshoot pipeline failures, data-quality anomalies, and performance bottlenecks, diagnosing root causes and implementing fixes without service disruption
• Validate that implemented pipelines meet data contracts, schema standards, and access-control policies defined by data architects and governance teams
• Optimize pipeline performance and cloud infrastructure costs by profiling job runtimes, partitioning strategies, and resource configurations

What you need

• 6–11 years in data science & ai
• SQL
• ETL
• AWS
• Python
• Spark
• R
• B.Tech or B.E. or B.Sc or BCA

Good to have

• CI/CD
• Git
• REST APIs
• GCP
• Azure
• Terraform