Senior Data Engineer

20.2k - 25.3k PLN20 240 - 25 300 PLN/ mies./ mies.UoPUmowa o pracę (brutto)

SeniorHybryda·WarszawaFull-time·Umowa o pracę

#473233·Dodano 2 dni temu·0

Źródło: nofluffjobs.com

Aplikuj teraz

Tech Stack / Keywords

Python

Podsumowanie oferty

As part of Bayer’s Data & AI Team, you will build and operate reliable data pipelines for clinical studies in the Clinical Data Lakehouse. The work supports timely, secure access to high-quality data for scientists, analysts, and AI agents, using Python and Databricks.

Wymagania

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 commitment to clear documentation, metadata and lineage publishing, and sustainable data engineering standards and practices.
Proficiency with Databricks, including DBX Asset Bundles, Lakeflow Jobs, Unity Catalog, access control and governance models, and Databricks CLI.
Experience with API design patterns and integrating data from source systems using interfaces such as OpenSharing/Delta Sharing, Iceberg-Sharing, ODBC, GraphQL, OData, REST, or event streaming.
Strong engineering skills in data engineering, software engineering, or cloud engineering.
Proficiency in Python, especially PySpark and Kapitan.
Experience with Git, including GitHub Actions, CI/CD pipelines using 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 such as GDPR and CCPA.
Cloud engineering experience, such as AWS or Azure.
Knowledge of the pharmaceutical domain, such as LOINC, SNOMED CT, omics, targets, assays, clinical studies, or RWE.

Obowiązki

Lead development and operation of reliable data pipelines to store, transform, share, and analyze clinical data, enabling an efficient clinical data flow in compliance with legal and regulatory requirements.
Collaborate with stakeholders in an agile setup to capture, specify, and address data-related requirements and dependencies, ensuring a fit-for-purpose technical implementation.
Exchange best practices with peers to maintain a coherent, consolidated, and scalable data landscape.
Contribute to integration patterns, FAIR data principles, and semantics to enable efficient, compliant, and secure data consumption by people, systems, and AI agents.
Collaborate with infrastructure experts on a robust, efficient, secure, and fit-for-purpose setup, leveraging infrastructure as code and composable architecture.
Mentor less-experienced colleagues and uphold standards in requirements specification, engineering practices, code review, testing, and documentation.

Bayer Sp. z o.o.

10 aktywnych ofert

Zobacz wszystkie oferty

Aplikuj teraz