Data Engineer

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.

Preferred/Plus

• Databricks, including Spark, Delta Lake, and Unity Catalog.
• Cloud data platforms such as Databricks, Snowflake, BigQuery, or Redshift.
• Job orchestration tools such as Airflow, Azure Data Factory, Prefect, or Dagster.
• Data quality frameworks and observability tools.
• Familiarity with BI ecosystems such as Power BI or Sigma.