Data Engineer

Requirements

• Seniority & Experience: Intermediate level with 3 to 5 years of hands-on experience in data engineering
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• Sector Experience (Bonus): Prior experience in the Tech or SaaS sector is a plus
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• Education: Master / Engineer in Computer Science, Engineering, or related field
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• Languages: Fluent in English and French
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• Core Engineering: Solid SQL & Modeling skills (efficient schemas) and hands-on experience with Python or Java
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• Cloud Platform : Experience with AWS, GCP, or Azure is required
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• Data Processing: Proven experience building robust ETL/ELT pipelines (GB/TB scale) with batch / streaming frameworks (e.g. Spark, Apache Beam, Flink, Hadoop) with automated quality checks and proactive monitoring
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• Orchestration : Experience with Dagster or Airflow (or equivalent)
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• Experience with Lakehouse or Data

  Warehouse is a plus (Snowflake, Big

  Query, Apache Iceberg / S3)
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• Engineering Standards: Ability to apply best practices to build maintainable pipelines while balancing technical debt with feature delivery (balancing speed and code quality)
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• AI usage: We value engineers who use AI-assisted tools (Cursor, Claude, Copilot)
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• Health & Privacy (Bonus): Interest in healthcare data and familiarity with GDPR/HDS. Previous exposure to FHIR is a plus
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• Pragmatic & Focused: Able to work in fast-paced environments with a focus on delivering value
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• Autonomous & Self-driven: Comfortable working independently while contributing effectively to cross-functional teams
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• Curious & Adaptable: Eager to learn and develop expertise in emerging data technologies
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• 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

• We are looking for an Data Engineer to join our Data Platform (Ingestion) team
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• Your mission is to help streamline data access to promote scalability as we transition from a web-centric to a data-centric design within cloud-based micro-services
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• Direct Report: Damien Parent (Lead Data Engineer)
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• You will be part of the Ingestion section of the Data Platform team, collaborating within a tech team of 8 people
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• Build and maintain scalable data ingestion pipelines and ETL/ELT processes (from staging to production)
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• Contribute to the evolution of our data architecture to improve performance, scalability, and reliability
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• Partner with analytics engineers, data scientists, and business teams to understand and implement data requirements
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• Support and optimize cloud-based data infrastructure (AWS)
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• Deploy automated data quality checks and monitoring systems to ensure data reliability
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• Develop and keep up-to-date technical documentation for data processes and systems
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• Investigate and resolve data-related issues to guarantee data integrity across the stack
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• The following is our current stack, we don’t expect you to be an expert in every single tool
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• Languages: Python, Java, TypeScript
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• Data Processing: Spark (GLUE), Apache Beam (or Apache Flink)
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• Storage & Table Format: PostgreSQL, Apache Iceberg, S3
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• Integration & Messaging: RabbitMQ
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• Infrastructure & Dev

  Ops: AWS, Terraform (Ia

  C), Docker, Kubernetes, Git

  Lab CI
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• Analytics & OLAP System : DBT, Cube, Metabase, Athena
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• Methodology: Agile (Scrum), Lean management