Data Engineer

• Architect, build, and maintain scalable, reliable data pipelines (batch & streaming) to ingest, transform, and deliver data for analytics, reporting, and ML use cases.
• Architect software applications, test, and build automated tools.
• Translate complex functional and technical requirements into architecture designs and high-performing software solutions.
• Select appropriate data solution software and define hardware requirements to support performance and scalability.
• Develop and implement standards and processes for data integration projects and initiatives.
• Lead the design and development of software applications, testing, and building tools.
• Optimize SQL queries (joins, window functions, aggregations, partitioning, indexing) and data schema performance.
• Design data models, schemas, and data warehouses/data lakes (dimensional, star, snowflake schemas, normalization/denormalization).
• Ensure data quality, correctness, and consistency across datasets (validation, anomaly detection, reconciliation).
• Ensure database changes are reviewed and approved according to standards.
• Monitor, troubleshoot, and tune performance of pipelines, databases, and workloads.
• Drive adoption of engineering best practices: version control, CI/CD, testing (unit and integration for data pipelines), documentation, and code reviews.
• Collaborate with software engineers to integrate data systems into production environments.
• Provide technical assistance to junior members and to colleagues across the company.
• Mentor and coach junior and mid-level engineers, promoting engineering discipline across the team.
• Evaluate and propose new tools, frameworks, and technologies for the data platform.
• Ensure data security, governance, access control, lineage, and compliance (e.g., GDPR, CCPA, internal standards).

Senior Data Engineer

Senior Data Developer, Data Engineering

Data Engineer

Senior Cloud Data Engineer – MLOps / Ingénieur·e senior en données Cloud – MLOps