Senior Data Engineer

Role Overview: We are looking for a Senior Data Engineer to integrate our teams in a challenging data modernisation context. This role is focused on the design, implementation and evolution of cloud-native data platforms, supporting large-scale analytical use cases and the migration from legacy systems to modern Lakehouse architectures. What you will do: - Design and implement modern data architectures based on Lakehouse principles using Databricks and/or GCP. - Develop scalable and reliable data pipelines for ingestion, processing and transformation, ensuring performance, cost efficiency and robustness. - Build and maintain ELT pipelines using Databricks, dbt and best practices for version control and CI/CD. - Orchestrate end-to-end data workflows using Apache Airflow, integrating with Databricks Jobs, BigQuery and cloud services. - Define and promote engineering standards, frameworks and guidelines covering security, governance, scalability and reusability. - Support and lead migration initiatives from legacy platforms (e.g. SAS, on‑prem databases, traditional ETL tools) to modern cloud-based data platforms. What you are like: - Proficient in cloud-based data platforms, preferably GCP (BigQuery, Cloud Storage, IAM, VPC) and/or Databricks on GCP or Azure. - Highly skilled in SQL (BigQuery / Databricks SQL) and experienced in Python and PySpark for distributed data processing. - Comfortable working with layered data architectures (raw/bronze, silver and gold). - Confident in influencing architectural decisions and acting as a technical reference within the team.