Senior Data Engineering Expert

Job Title

We are building the future of healthcare analytics. Our goal is to create pipelines that are reliable, observable and continuously improving in production.

• Design, build and maintain scalable ETL pipelines using Python (Pandas, PySpark) and SQL, orchestrated with Airflow.
• Develop and maintain the SAIVA Data Lake / Lakehouse on AWS, ensuring quality, governance, scalability and accessibility.
• Run and optimize distributed data processing jobs with Spark on AWS EMR and / or EKS.
• Implement batch and streaming ingestion frameworks (APIs, databases, files, event streams).
• Enforce validation and quality checks to ensure reliable analytics and ML readiness.
• Monitor and troubleshoot pipelines with CloudWatch, integrating observability tools like Grafana, Prometheus or Datadog.
• Automate infrastructure provisioning with Terraform, following AWS best practices.
• Manage SQL Server, PostgreSQL and Snowflake integrations into the Lakehouse.
• Participate in an on-call rotation to support pipeline health and resolve incidents quickly.
• Write production-grade code, and contribute to design / code reviews and engineering best practices.

Requirements

We require strong technical skills from our team members :