Senior Solution Architect (Scientific Data Platform)
L
Link GroupBiotech Pharma R&D
Workplace type: remote; Locations: Warszawa, -, Gdańsk, -, Kraków, -, Wrocław, -, Poznań, -, Lublin, -, Łódź, -, Białystok, -, Olsztyn, -, Szczecin, -, Warszawa, Country code: PLFull-TimeSenior
Salary23520 - 28560 PLN per hour b2b currencySource=original; 5139 - 6240 CHF per hour b2b currencySource=conversion; 5441 - 6607 EUR per hour b2b currencySource=conversion; 4673 - 5674 GBP per hour b2b currencySource=conversion; 6311 - 7664 USD per hour b2b currencySource=conversion
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Job Details
- Languages
- English (B2 level required)
- Required Skills
- Microsoft AzureDatabricks
Requirements
- Proven experience as a Solution Architect delivering technology solutions in pharma, biotech, or life sciences R&D.
- Strong understanding of scientific/discovery data workflows.
- Proven experience designing data mesh and/or data product architectures.
- Deep, hands-on experience with Microsoft Azure and Databricks.
- Experience integrating ELN, LIMS, laboratory systems, and scientific instruments.
- Strong knowledge of metadata management, semantic modelling, data lineage, and data standards.
- Practical experience applying FAIR principles and data governance.
- Experience working with structured and unstructured scientific data.
- Understanding of AI/ML data enablement requirements.
- Experience working in regulated life sciences environments (GxP vs non-GxP).
- Strong stakeholder management and influencing skills in a matrix environment.
- Professional fluency in English (B2 level).
Responsibilities
- Define and maintain the end-to-end target architecture across scientific data workflows.
- Design data mesh and data product architectures, including ownership, data contracts, and quality expectations.
- Design cloud data solutions using Microsoft Azure and Databricks, including lakehouse/Delta architectures and secure data pipelines.
- Define integration architectures connecting ELN, LIMS, sample inventory systems, and scientific instruments.
- Architect solutions for structured and unstructured scientific data, including high-volume instrument outputs and provenance.
- Operationalise FAIR data principles to support cataloguing, discoverability, and stewardship.
- Ensure scientific data is structured and exposed to enable AI/ML use cases and feature pipelines.
- Apply appropriate data integrity and regulatory controls across GxP and non-GxP R&D environments.
- Collaborate with scientists and business SMEs to translate experimental workflows into scalable technical solutions.
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