Data Analytics Engineer

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)
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• Experience working with relational and analytics databases (Postgre

  SQL, Athena, Big

  Query, or equivalent)
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• Fluent in English and French
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• SQL Mastery: You write "clean" SQL, understand window functions, indexing strategies, and know how to optimize complex queries
,
• Data Architecture: Deep understanding of Lakehouse architectures and dimensional modeling
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• ELT: Deep hands-on experience designing and scaling ELT pipelines, with an expert-level mastery of DBT to transform raw data into high-quality analytical assets
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• Software Engineering Mindset: You write production-grade Python code, applying software best practices to data
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• Governance Advocate: Strong commitment to metadata management, lineage, and documentation
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• AI-Assisted: Ability to leverage tools like Cursor or Claude to accelerate delivery while maintaining high code quality
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• Collaborative mindset and Team player : Strong communication skills and a genuine passion for teamwork + Dedicated to elevating your colleagues and fostering collective success
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• Self-driven & autonomous: Comfortable working independently while contributing to cross-functional teams
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• Curiosity & adaptability: Eager to learn and develop expertise in emerging technologies
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• Problem-solving orientation: Proactive approach with strong analytical and prioritization skills
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• Quality-focused: Committed to code quality, testing, and documentation
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• A Note on Applying: We know the perfect candidate doesn't exist. If you believe you possess the core required experience and strongly align with this mindset, we highly encourage you to apply

What the job involves

• Joining the Data Platform Team, reporting to the Lead Data Engineer, your mission is to participate in facilitating access to data in order to promote scalability
,
• The Data Analytics Engineer sits at the crossroads of software engineering and data analysis, ensuring our Lakehouse is the "single source of truth" for our Data Scientists and Business Stakeholders
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• Direct Report: Damien (Data Engineer Manager)
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• Collaboration: You will be part of the Analytics section of the Data Platform team, collaborating within a tech team of 8 people
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• Data Modeling: Design and implement robust dimensional models (Star Schema) within our Apache Iceberg Lakehouse to support business reporting and
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• Transformation Pipelines: Build and optimize modular SQL/Python transformations using dbt and Dagster, ensuring code reusability and maintainability
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• Data Governance & Lineage: Implement and maintain DataHub to provide end-to-end lineage, a searchable data catalog, and clear ownership of data assets
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• Semantic Layer: Develop and manage our semantic layer via cube dev to provide unified data definitions across the company
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• Data Quality & Traceability: Implement automated tests and monitoring to guarantee data integrity and observability from S3 to Metabase
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• Performance Optimization: Fine-tune AWS Athena queries and Iceberg table layouts (partitioning, compaction) to ensure fast and cost-effective analytics
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• Documentation: Maintain up-to-date documentation of data models and definitions in DataHub
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• Run & Support: Investigate and resolve data quality incidents to ensure the reliability of our analytical platform
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• To succeed in your mission, you will be part of a skilled and collaborative team working with modern data technologies. We encourage continuous learning and innovation, with dedicated time for experimentation and skill development