Design and implement robust dimensional models (Star Schema) within our Apache Iceberg Lakehouse to support business reporting.
Build and optimize modular SQL/Python transformations using dbt and Dagster, ensuring code reusability and maintainability.
Implement and maintain DataHub to provide end-to-end lineage, a searchable data catalog, and clear ownership of data assets.
Develop and manage our semantic layer via cube dev to provide unified data definitions across the company.
Implement automated tests and monitoring to guarantee data integrity and observability from S3 to Metabase.
Fine-tune AWS Athena queries and Iceberg table layouts (partitioning, compaction) to ensure fast and cost-effective analytics.
Maintain up-to-date documentation of data models and definitions in DataHub.
Investigate and resolve data quality incidents to ensure the reliability of our analytical platform.

Requirements

Master’s degree in Computer Science, Data Engineering, or a related quantitative field.
3+ years of experience in a Data Engineering or Analytics Engineering role.
Strong interest in the healthcare sector and the challenges of medical data normalization (HL7, FHIR).
Experience working with relational and analytics databases (PostgreSQL, Athena, BigQuery, or equivalent).
Fluent in English and French.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythondbtDagsterApache IcebergAWS AthenaPostgreSQLBigQuerydata modelingautomated testing

Soft Skills

communicationproblem-solvingattention to detailcollaborationdocumentation

Certifications

Master’s degree in Computer ScienceMaster’s degree in Data Engineering