DICK’S Sporting Goods is committed to creating an inclusive and diverse workforce while positively impacting lives through sports. The Analytics Engineer II will design and build data models and BI dashboards to solve business problems, collaborating with various teams to translate technical and business concepts into actionable data solutions.
Responsibilities:
- Understand the basics for modeling and is able to implement best practices for data visualization. Design performant data models using SQL and BI development tools
- Collaborate and work as part of an Agile team with Product Managers, Analysts, Analytics Engineers, and Data Engineers to understand data and business needs. Translate technical and business concepts and apply data and BI solutions
- Understand how to work within an established program management plan to achieve specific goals. Support and maintain production processes and effectively troubleshoots issues. Coordinate code review with engineering, data validation and QA/UAT with analysts and business partners
- Design, build, and deploy new data models and BI applications and enhance existing in production. Support efforts and suggest ways to optimize solutions to better meet business, performance, and/or quality needs
- Develop own capabilities by participating in assessment and development planning activities as well as formal and informal training and coaching
Requirements:
- Experience with Business Intelligence (BI) tools (e.g. Microsoft Power BI, QlikSense, Looker, Tableau)
- Experience with cloud platforms (e.g. Microsoft Azure, Google Cloud Platform (GCP))
- Experience with cloud data warehouses (e.g. Snowflake, Google BigQuery)
- Experience with databases (e.g. Oracle)
- Experience with version control systems and CI/CD (e.g. GitHub, GitHub Actions)
- Development experience in SQL
- 1-3 Years of Experience
- Bachelor's Degree or Equivalent Level Preferred
- Databricks – Unity Catalog, SQL stored procedures, job orchestration, Databricks Asset Bundles (DABs), Metric Views, Genie
- Power BI – report/dashboard development, DAX measures, data modeling, Power Query
- SQL – advanced patterns including CTEs, MERGE/upsert, window functions, parameterized stored procedures, dimensional modeling
- Python – PySpark, notebook-based ETL workflows
- Retail/merchandising analytics domain knowledge