Data Engineer

📋 Description

• Take operational ownership of the usage and adoption pipelines and their alerting.
• Reconcile figures derived from our product-usage tool.
• Separate development and production environments and mature CI/CD so deployment is repeatable and
• Build and maintain Bronze-to-Gold pipelines in Databricks, Unity Catalog metric views, and the
• Extend automated data quality checks across the underlying gold data layers and validate outputs
• Collaborate with Product and Post-Sales teams to prioritize usage and adoption signals, including

🎯 Requirements

• 3-5 years' professional experience building and operating production data pipelines (ETL/ELT) in a
• Hands-on Databricks proficiency: Unity Catalog, Spark Declarative Pipelines, and metric tables
• Strong SQL and Python applied to data engineering work.
• Experience with data transformation/orchestration tooling such as Spark Declarative Pipelines, dbt
• Solid grounding in data modeling (dimensional/star-schema approaches) for analytics consumption.
• Git-based version control and CI/CD practices applied to data pipelines, not just application code.

🎁 Benefits

• Equal opportunity employer.
• Commitment to diversity and inclusion.
• Opportunity to work on impactful projects.