Description
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.
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 colleagues and uphold high standards in requirements specification, engineering practices, code review, testing, and documentation.
Requirements
•Bachelor's degree in computer science, data science, information technology, or a related field.
•5+ 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.
Nice to have
•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.)
Conditions
•The minimum monthly gross compensation for this role is 20,240 PLN, with final pay determined based on objective factors such as experience, qualifications, scope of responsibility, and internal alignment.
•This position is eligible for variable pay components, such as performance-based bonuses, awarded in accordance with the applicable employee group, role scope, and compensation structure.
•Medical care above statutory requirements.
•Flexible benefits supporting leisure, and well-being/sports programs.
•Life, accident, and disability insurance through group coverage.
•Employer-supported pension plans with regular company contributions.
•Home office allowance to support hybrid or remote work.
•Company car provided (as a working benefit).
•Extra paid holidays.
•Bayer offers the possibility of working in a hybrid model. Employees can work from home, from the office, or combine both work environments. The possibilities of using the hybrid model are each time discussed with the manager.
