Data Engineer

Data Engineer with 4 years of experience, specializing in building, migrating, and optimizing scalable, production-grade data pipelines for enterprise-level organizations. My core technical expertise lies within native Databricks, PySpark, and Python, backed by solid experience across major Cloud environments (Azure, GCP) and automated CI/CD practices. Operating as an independent contractor, I deliver immediate value to data teams looking for an autonomous, business-oriented engineer who thrives in fast-paced Agile environments.

🛠️ CORE COMPETENCIES & TECH STACK: • Data Engineering: Databricks (Lakehouse Fundamentals Certified), PySpark, Spark SQL, Python, ETL/ELT pipelines • Cloud & Data Warehousing: Azure, Google Cloud Platform (GCP), Snowflake, BigQuery • DevOps & MLOps: CI/CD (GitLab-CI, Azure DevOps), Docker, Version Control (Git) • Data Governance & BI: DataGalaxy, Dataiku, PowerBI

🎯 KEY PROJECTS TO DATE: • Direct Assurance (Insurance): Led the production migration from R to PySpark on a native Databricks Lakehouse (Medallion architecture: Silver to Gold layer). Designed and automated end-to-end batch workflows (Trigger mode) to deliver business-critical Datamarts handling millions of rows and hundreds of columns. • Franprix (Retail): Developed automated reporting pipelines using Python and Snowflake; established data governance mapping for an enterprise POC (DataGalaxy). • Stellantis / Google (Automotive/Tech): Engineered OOP Python scripts to automate international tracking tools and GTM data containers migration across global markets.

Available for full remote contracts across Europe. Let's discuss your data engineering challenges: [email protected]