Design, build, and govern cloud-based data platforms that turn heterogeneous, multi-country life-sciences data into trusted, reusable data products.
The role spans clinical trial data, real-world data (RWD), and omics — harmonising these into standardised, regulatory-grade, analysis-ready assets. Combines hands-on engineering on Azure and Databricks with technical leadership of a multidisciplinary team.
Requirements
Required (Must-Have)
- 8+ years in data engineering, with substantial Life Sciences / pharmaceutical experience.
- Proven delivery of cloud data platforms on Azure and Databricks; familiarity with Microsoft Fabric.
- Strong proficiency in Python and SQL, plus ETL/ELT orchestration (Azure Data Factory).
- Hands-on experience with CDISC standards (SDTM, ADaM) and clinical data workflows.
- Relational and non-relational stores: SQL Server, PostgreSQL, MongoDB.
- Data governance, access control, and sensitive/anonymised data handling.
- Team leadership and Agile delivery (Scrum, SAFe, Kanban).
Preferred (Nice-to-Have)
- OMOP CDM and real-world data standardisation experience.
- Omics / bioinformatics data and large-scale scientific datasets.
- Graph databases (Neo4j) and knowledge-graph modelling.
- BI & visualisation: Power BI, Metabase, Streamlit.
- Certifications (Preferred) Databricks Certified Data Engineer (Associate / Professional) Microsoft Certified: Azure Data Engineer / Fabric Analytics Engineer Associate Neo4j Certified Professional Professional Scrum Master (PSM I / II)
Soft Skills
- Cross-functional collaboration with scientific and business stakeholders.
- Clear communication of technical concepts to non-technical audiences.
- Multilingual capability for global study support (an asset).
Team leadership and Agile delivery (Scrum, SAFe, Kanban)
Strong proficiency in Python and SQL
clinical data workflows
Pharmaceutical experience
ETL/ELT orchestration
SQL Server, PostgreSQL, MongoDB
Proven delivery of cloud data platforms on Azure and Databricks
8+ years in data engineering
Azure DataFactory
Data governance, access control, and sensitive/anonymised data handling
Hands-on experience with CDISC standards (SDTM, ADaM)
Microsoft Fabric
Preferred skills
OMOP CDM and real-world data standardisation experience
Omics / bioinformatics data and large-scale scientific datasets
BI & visualisation: Power BI, Metabase, Streamlit
Graph databases (Neo4j) and knowledge-graph modelling
Skills Required
- 8+ years in data engineering with substantial Life Sciences / pharmaceutical experience
- Proven delivery of cloud data platforms on Azure and Databricks; familiarity with Microsoft Fabric
- Strong proficiency in Python and SQL
- ETL/ELT orchestration experience (Azure Data Factory)
- Hands-on experience with CDISC standards (SDTM, ADaM) and clinical data workflows
- Experience with relational and non-relational stores: SQL Server, PostgreSQL, MongoDB
- Data governance, access control, and sensitive/anonymised data handling
- Team leadership and Agile delivery (Scrum, SAFe, Kanban)
- OMOP CDM and real-world data standardisation experience
- Omics / bioinformatics data and large-scale scientific datasets
- Graph databases (Neo4j) and knowledge-graph modelling
- BI & visualisation: Power BI, Metabase, Streamlit
- Relevant certifications (Databricks Data Engineer, Microsoft Azure Data Engineer / Fabric Analytics Engineer, Neo4j Certified, PSM)
What We Do
Belmont Lavan is an IT solutions provider specializing in the design, development, and implementation of systems like ERP, CRM, EAM, Microsoft, and Cybersecurity, aiming to help businesses streamline operations, enhance security, and improve efficiency.
