Join a mission-driven health technology company building a global evidence network
Part of a core data engineering team responsible for designing and operating pipelines
Ingest, transform, and standardize real-world health data
Translate complex source data structures into recognized healthcare data standards (FHIR, OMOP-CDM)
Ensure data quality, security, and scalability across the platform
Work in a fast-paced, engineering-led environment

Advanced SQL skills — complex transformations, performance optimization, data modeling
Strong Python proficiency for pipeline development and automation
Proven senior-level track record as a Data Engineer, with experience scaling data products from pilot to production
Hands-on experience building and optimizing big data pipelines, architectures, and datasets using tools such as Apache Airflow and/or Apache Spark
Experience with AWS technologies (Redshift, S3, or equivalent managed services)
Strong analytical skills when working with unstructured and semi-structured datasets
Solid understanding of data science and Big Data concepts
Excellent written and verbal communication skills in English (B2+)
Self-driven, ownership mentality, proactive approach to problem-solving
NICE TO HAVE (Preferred) Experience with health data frameworks: OMOP-CDM and/or FHIR
Familiarity with additional stack components: Dagster, Trino, ClickHouse, Airbyte
Experience with data quality assurance, writing test specifications and test case scenarios
Background working in healthcare or life sciences data environments
Experience in agile/continuous delivery engineering teams

Data Engineer – Apache Airflow, Spark, AWS

Key skills