At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Data Engineer 

POSITION PURPOSE:

We are seeking a Data Engineer to join Bayer's Enterprise Data & Analytics Platform team. As an integral part of the team, you will build robust, scalable, high-performance data products with strong metadata management, data lineage, and operational rigor. You will operationalize data solutions-from concept to reliable production-ensuring precision, traceability, and excellence, to fuel the agentic transformation of Bayer's corporate functions.

YOUR TASKS AND RESPONSIBILITIES:

Efficient Data Pipeline Implementation

• Design and implement efficient data pipelines that integrate information from various sources and business domains. The goal is to develop globally harmonized data models and perform KPI calculations, ensuring consistency and accuracy across the organization.

Data Management and Quality Assurance

• Contribute to the definition and establishment of data management and data quality standards. Ensure that all data is well-managed to build stable, reusable, and quality-assured data assets, supporting long-term business needs.

Agentic-ready data products (structured and unstructured)

• Help build the data foundation of the agentic transformation. Collaborate with data scientists and business subject matter experts to enhance existing structured data products and pioneer the development of unstructured data products - making them ready for GenAl integration and advanced analytics use cases.

Data Protection and Compliance

• Ensure that all data products adhere to established data protection and compliance standards. Implement effective data access management policies, data privacy policies, and secure provisioning of data in accordance with corporate guidelines.

Continuous Framework Enhancement

• Continuously improve and enhance implementation frameworks based on the evolving needs of analytics products that consume the data assets under your responsibility.

Team Guidance and Task Management

• Provide guidance to other data engineers, both internal and external, ensuring that all team members apply consistent design principles and maintain high code quality. Break down larger work packages into manageable tasks to facilitate efficient project execution.

Metadata Management and Data Lineage

• Architect and maintain comprehensive metadata frameworks that support seamless data discovery, governance, and traceability.
• Implement automated data lineage tracking to ensure transparency and control across all data assets.

WHO YOU ARE:

• Bachelor/Master's degree in Computer Science, Business Informatics, Math, Engineering, or a related field.
• 5+ years of working experience in the field of Data & Analytics
• 5+ years of experience working with Databricks
• 5+ years of proficient coding experience with Python for data engineering, including SQL and PySpark (DataFrame API, Spark SQL, MLlib), with hands-on experience in various databases (SQL/NoSQL), key libraries (e.g., pandas, SQLAlchemy), parallel processing and advanced data transformation and performance optimization techniques while ensuring code modularity, reusability, and maintainability.
• Prior experience and knowledge of Azure cloud is a must. Basic knowledge of AWS is also desirable.
• Excellent data engineering & technology knowledge (Azure Data Lake Gen2, Azure Data Factory and Databricks as well as data management knowhow (data cataloguing, data quality management)
• Solid understanding of data modeling, ETL processing and lakehouse concepts.
• Basic understanding of GenAl, AgenticAl, and Machine Learning
• Experience with non-structured data assets, such as documents and parsing/transformation methods, is desirable. Also, familiarity with Vector Databases is a plus
• Profound knowledge of CI/CD processes and tools (GitHub VCS, GitHub Actions, Azure DevOps Pipelines)

Ever feel burnt out by bureaucracy? Us too. That's why we're changing the way we work- for higher productivity, faster innovation, and better results. We call it Dynamic Shared Ownership (DSO). Learn more about what DSO will mean for you in your new role here

https://www.bayer.com/enfstrategyfstrategy

Bayer does not charge any fees whatsoever for recruitment process. Please do not entertain such demand for payment by any individuals / entities in connection with recruitment with any Bayer Group entity(ies) worldwide under any pretext.

Please don’t rely upon any unsolicited email from email addresses not ending with domain name “bayer.com” or job advertisements referring you to an email address that does not end with “bayer.com”. For checking the authenticity of such emails or advertisement you may approach us at HROP_INDIA@BAYER.COM.