Belmont Lavan

Belmont Lavan

Belmont Lavan Talent Without Borders | PEO & Talent Acquisition Partner Belmont Lavan is a PEO and Talent Acquisition Global Service provider WORKING WITH STARTUPS & CORPORATES INTERNATIONALLY EUROPE USA CANADA AFRICA WORKING WITH STARTUPS & CORPOR...

Professional Services
11-50
Founded 2001

Description

  • Design, build, and govern cloud-based data platforms on Azure and Databricks.
  • Harmonise heterogeneous, multi-country life sciences data into standardised, analysis-ready assets.
  • Develop data products spanning clinical trial data, real-world data, and omics datasets.
  • Lead technical delivery for a multidisciplinary team.
  • Implement ETL/ELT pipelines and orchestration using Azure Data Factory.
  • Apply data governance, access control, and secure handling of sensitive and anonymised data.
  • Work with clinical data workflows and CDISC standards to support regulatory-grade outputs.
  • Collaborate with scientific and business stakeholders to translate data needs into technical solutions.
  • Support Agile delivery processes across Scrum, SAFe, or Kanban.

Requirements

  • 8+ years of experience in data engineering, with substantial life sciences or pharmaceutical experience.
  • Proven delivery of cloud data platforms on Azure and Databricks, with familiarity with Microsoft Fabric.
  • Strong proficiency in Python and SQL.
  • Hands-on experience with ETL/ELT orchestration using Azure Data Factory.
  • Hands-on experience with CDISC standards, including SDTM and ADaM, and clinical data workflows.
  • Experience with relational and non-relational data stores, including SQL Server, PostgreSQL, and MongoDB.
  • Experience in data governance, access control, and handling sensitive or anonymised data.
  • Experience leading teams and delivering work in Agile environments such as Scrum, SAFe, or Kanban.
  • Preferred experience with OMOP CDM and real-world data standardisation.
  • Preferred experience with omics or bioinformatics data and large-scale scientific datasets.
  • Preferred experience with graph databases such as Neo4j and knowledge-graph modelling.
  • Preferred experience with BI and visualisation tools such as Power BI, Metabase, or Streamlit.
  • Preferred certifications include Databricks Certified Data Engineer, Microsoft Azure Data Engineer or Fabric Analytics Engineer Associate, Neo4j Certified Professional, or PSM I/II.
  • Strong communication skills for working with technical, scientific, and non-technical stakeholders.
  • Multilingual capability for global study support is an asset.

Interested in this position?

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