Analytics Engineer II
Role details
Job location
Tech stack
Job description
Data Modeling & Visualization
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.
Functional/Technical Requirements
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.
Program/Portfolio Management Support
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.
Technical Developments Recommendation
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.
Ongoing Learning and Development
Develop own capabilities by participating in assessment and development planning activities as well as formal and informal training and coaching., At DICK'S, we thrive on innovation and authenticity. That said, to protect the integrity and security of our hiring process, we ask that candidates do not use AI tools (like ChatGPT or others) during interviews or assessments.
To ensure a smooth and secure experience, please note the following:
- Cameras must be on during all virtual interviews.
- AI tools are not permitted to be used by the candidate during any part of the interview process.
- Offers are contingent upon a satisfactory background check which may include ID verification.
If you have any questions or need accommodations, we're here to help. Thanks for helping us keep the process fair and secure for everyone!
Requirements
Technology Experience
Experience with Business Intelligence (BI) tools (e.g. Microsoft Power BI, QlikSense, Looker, Tableau); cloud platforms (e.g. Microsoft Azure, Google Cloud Platform (GCP)); cloud data warehouses (e.g. Snowflake, Google BigQuery); databases (e.g. Oracle); version control systems and CI/CD (e.g. GitHub, GitHub Actions). Development experience in SQL. Python development and data architecture experience preferred.
Preferred experience with:
- 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, * Bachelor's Degree or Equivalent Level Preferred, * 1-3 Years of Experience