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About the Role

We are looking for a Senior Data Engineer to lead the design and implementation of a modern analytical platform and data warehouse in the health and life sciences domain.

You will collaborate closely with development teams and scientific stakeholders, shaping architecture decisions, building core data pipelines, and defining canonical data models for complex biological datasets. This role requires someone who can operate at both strategic and hands-on levels, effectively bridging scientific and engineering teams.

Key Responsibilities

• Design and implement data architecture and warehouse solutions
• Build and maintain ETL pipelines using Python and SQL
• Develop and optimize a ClickHouse-based analytical platform
• Define canonical models for biological data (traits, genes, phenotypes, variants)
• Ensure data provenance, lineage, and reproducibility
• Implement dbt-based transformation and release workflows
• Collaborate with stakeholders on data products and architecture trade-offs
• Optimize performance for large-scale datasets (2TB+)
• Work with Parquet ingestion pipelines (Spark if needed)

Requirements

• 6+ years of experience in Data Engineering
• Strong expertise in Python, SQL, and ETL pipelines
• Experience with at least two data warehouses: Snowflake, Amazon Redshift, ClickHouse
• Solid understanding of data modeling and analytical platforms
• Hands-on experience with dbt
• Experience optimizing high-volume analytical workloads
• Ability to make architecture decisions and trade-offs
• Strong communication skills with cross-functional teams