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Lead Analytics Engineer

Dick's Sporting Goods LogoDick's Sporting Goods
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Location

Remote

Job Responsibilities:

Data Modeling and Visualization

  • Drive the design of highly complex data models and BI applications to enable easy consumption and analysis.
  • Select appropriate data and BI tools and technologies to implement solutions, implementing and documenting industry best practices to be used by the team.

Functional/Technical Requirements

  • Leverage advanced experience, knowledge, and skillset in Analytics Engineering and data domain to drive functional and technical requirements for Analytics Engineering as part of an Agile team with Product Managers, Analysts, Analytics Engineers, and Data Engineers.
  • Act as a SME for data and business needs within domain.

Program/Portfolio Management Support

  • Contribute to the management of a portfolio of programs while reporting to and in partnership with senior teammates.
  • Support production processes and advise team on troubleshooting and resolutions to reduce incidents.
  • Train engineering teammates in coding, data modeling, and BI development best practices and conduct code review ensuring repeatable and easy-to-maintain processes are implemented amongst the team.

Technical Developments Recommendation

  • Discuss and recommend advanced and innovative data and BI solutions to better meet business, performance, and/or quality needs.
  • Recognize opportunities for better process improvements and work with senior teammates to implement.

Ongoing Learning and Development

  • Explore and develop detailed understanding of external developments or emerging issues and evaluate impact to the organization and team. Identify gaps in current solutions and BI tools and technologies.
  • Recommend new technologies needed to accelerate the business.
  • Develop cost/benefit analysis and assist in implementation of new tools and platforms.

Technology Experience

  • Expert-level experience with: Business Intelligence (BI) tools (e.g. Microsoft Power BI, Qlik Sense, 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)
  • Expert development experience in SQL required.
  • Fully competent-level of Python development and data architecture experience preferred.

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