Senior Data Engineer

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.

Senior Data Engineer

POSITION PURPOSE:

As a Senior Data Engineer, you are part of Bayer's Data & AI Team with a focus on creating data solutions that provide timely, high-quality data to scientists, analysts, and AI agents. You will closely collaborate with experts from business and IT to design, implement and operate reliable GxP-validated data pipelines that enable timely and secure access to high-quality data for clinical studies in our Clinical Data Lakehouse, combining a solid understanding for the clinical data flow with excellent technical and conceptual skills.

YOUR TASKS AND RESPONSIBILITIES:

Lead the development and operation of reliable data pipelines to store, transform, share and analyze clinical data, enabling an efficient clinical dataflow in compliance to legal and regulatory requirements.

Collaborate closely with relevant stakeholders in an agile setup to capture, specify and address data-related requirements and dependencies to ensure a fit-for-purpose technical implementation in a healthy data ecosystem.

Actively exchange with peers, embracing and applying best-practices to maintain a coherent, consolidated and scalable data landscape.

Contribute to the design and implementation of integration patterns, FAIR data principles and semantics to enable efficient, compliant, and secure data consumption by humans, systems, and AI agents within and beyond the primary data context.

Collaborate with infrastructure experts to ensure a robust, efficient, secure and fit-for-purpose setup, leveraging infrastructure-as-code and composable architecture.

Mentor less-experienced collagues and uphold high standards in requirements specification, engineering practices, code review, testing, and documentation

WHO YOU ARE:

Required -

Bachelor’s degree in computer science, data science, information technology, or a related field.

8+ years of experience in data engineering, data operations, or a similar role, delivering production-grade data pipelines and services

Strong ownership of deliverables, high standards for code review and peer mentorship, and a commitment to clear documentation, metadata/lineage publishing, and sustainable data engineering standards and practices

Proficiency with Databricks, including DBX Asset Bundles, Lakeflow Jobs, Unity Catalog, Access control and governance model and Databricks CLI

Experience with API design patterns and Ability to integrate data from source systems using various interface patterns, such as OpenSharing/Delta Sharing, Iceberg-Sharing, ODBC, GraphQL, OData, REST, or event streaming

Strong engineering skills (data engineering, software engineering, or cloud engineering)

Proficiency in Python programming, especially PySpark and Kapitan

Experience in Git, including Github Actions, CI/CD Pipelines (declarative YAML), Branching strategies, and trunk-based development

Understanding of data security principles and practices

Strong analytical and communication skills

Good communication and collaboration abilities to work independently in a self-organized team

High level of accuracy and attention to detail

Preferred –

Experience with GxP validation and Computerized Systems Validation

Experience in Requirements Engineering

Hands-on experience with Infrastructure-as-code, ideally Terraform on AWS

In-depth knowledge of FAIR Data Principles, Linked Data principles, and Data Mesh architecture concepts, with demonstrated ability to apply them in practice

Experience with semantic layer concepts in modern data platforms such as Databricks, Snowflake, or Microsoft Fabric

Experience designing and implementing Model Context Protocol (MCP) servers

Hands-on experience with GraphRAG solution design and implementation

Knowledge of data privacy regulations (e.g., GDPR, CCPA)

Cloud engineering experience (e.g. AWS, Azure)

Knowledge in the pharmaceutical domain (e.g. LOINC, SNOMED CT, omics, targets, assays, clinical studies, RWE, etc.)

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 [email protected].

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YOUR APPLICATION|

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Bayer is an equal opportunity employer that strongly values fairness and respect at work. We welcome applications from all individuals, regardless of race, religion, gender, age, physical characteristics, disability, sexual orientation etc. We are committed to treating all applicants fairly and avoiding discrimination.

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Location:| India : Karnataka : Bangalore |

Division:| Enabling Functions |

Reference Code:| 894553 | |

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