Architect and build ELT/ETL pipelines ingesting data from APIs, applications, databases, and SaaS platforms into Databricks
Own bronze and silver layers using PySpark, SQL, and medallion architecture best practices
Implement automated testing, monitoring, alerting, and data quality frameworks to ensure pipeline reliability
Develop reverse ETL pipelines to move curated data back into operational systems
Partner with Analytics Engineers, BI teams, and stakeholders to define data contracts and integrate new sources
Champion data governance, security standards, and engineering best practices across the organization

3+ years of data engineering or software engineering experience
Advanced SQL and Python expertise with proven ability to write efficient, scalable code
Hands-on Databricks experience and strong understanding of medallion architecture
Familiarity with GitHub, version control workflows, and automated testing practices
Understanding of data quality frameworks and experience working in Agile/Scrum environments
Occasional travel necessary to accommodate for the global and regional meetings / workshops
Ability to occasionally join calls before / after traditional office hours

Data Engineer

Key skills