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Common senior data engineer title, 4+ years band, broad Databricks/Spark/Python skills, likely metro.
Core data engineering skills are widely transferable across industries despite retail domain as nice-to-have.
Explicit 4+ years plus mandatory Databricks/Spark/Python/SQL and CI/CD expectations increase screening rigidity.
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Design, build, and maintain scalable data pipelines on Databricks using SQL and Python within an agile product team.
Collaborate with data scientists, software developers, and analysts to deliver high-quality data solutions meeting business needs.
Report to Principal/Lead Data Engineer and contribute to ETL/ELT solutions including data extraction, transformation, cleansing, integration, and management.
4+ years experience with Big Data technologies including Apache Spark™, Cloud Native, Data Lakes, and Databricks.
Strong Python skills for automation and unit testing with frameworks like Nutter, Unittest, or Pytest.
Strong SQL skills including complex queries and performance tuning experience.
Experience with version control systems like Git and CI/CD processes.
Experienced working in large cross-functional teams with effective communication abilities.
Familiarity with data modeling, data warehousing, and data integration best practices.
Preferably has experience with retail domain concepts, Build-Operate-Transfer (BOT) model, Azure cloud platform, and real-time data processing.