FORMAL JOB DESCRIPTION:
As a Data Engineer, you'll partner closely with our Principal Data Engineers to keep data pipelines healthy, resolve bugs, and deliver well-modeled, trusted data for reporting and analytics. You'll spend most of your time writing SQL and Python, designing and optimizing database models, and helping deliver trusted certified data that power dashboards, self-service analytics, and data science. The ideal candidate will have experience working with Databricks and medallion architecture, including Bronze, Silver, and Gold data layers. Experience applying data engineering best practices for data quality, performance, testing, monitoring, documentation, and maintainability is important. Experience with retail or wholesale distribution data-such as sales, inventory, merchandising, logistics, and supply chain-is strongly preferred. Top Skills Details Databricks SQL Python Medallion architecture (Bronze, Silver, and Gold) Additional Skills & Qualifications Operational mindset with strong debugging and root-cause analysis skills. Clear and concise communicator who can translate business needs into technical tasks. Collaborative, service-oriented teammate who is comfortable partnering with Principal Data Engineers and supporting analysts. Organized and detail-oriented, with strong documentation habits. Familiarity with Agile/Scrum and the software development lifecycle. Experience applying data engineering best practices, including version control, code reviews, automated testing, monitoring, and performance optimization.
Required:
Strong SQL skills, including advanced joins, window functions, CTEs, and performance tuning. Python experience for data processing and automation using pandas or PySpark. Hands-on database and data warehouse modeling experience, including dimensional and normalized modeling. Experience developing and supporting data pipelines using a medallion architecture with Bronze, Silver, and Gold layers. Understanding of data quality, testing, monitoring, and production support best practices. Experience working with retail data domains such as sales, inventory, products, pricing, merchandising, replenishment, logistics, or supply chain is preferred.
