Senior Data Engineer (REMOTE)

Dick's Sporting Goods

Dick's Sporting Goods

Data Science
United States · Remote
Posted on Tuesday, June 6, 2023

At DICK’S Sporting Goods, we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve.

If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today!


At Dicks Sporting Goods we are creating the future of sports, driven by powerful data products and platforms that serve our Athletes and Teammates.

We are looking for a Senior Data Engineer to join our passionate team, adding your background and experience making us even stronger. In this role, you will build dataset and make them accessible to our partner teams by writing great code to simplify the complexity and ensure quality. Your work will enable product teams, data science, and decision-makers across the company to bring together insights and inform our business.

At Dick’s Sporting Goods are constantly seeking to improve ourselves. We believe that trusted, easy to consume data is the critical and as a Senior Data Engineer your work will help to build that foundation.

What You Will Do

  • Design, develop, reliable data models and extremely efficient pipelines to build quality data and provide intuitive analytics to our partner teams.

  • Make data more discoverable and easier to use for Data Scientists, Analysts and Other Product teams across the company.

  • Mentor and Lead engineering teams and team members in software delivery within Data in an Agile Environment

  • Own Data Domains and Data Solutions across entire life cycle while utilizing strong problem-solving ability.

  • Participate in design sessions and code reviews to elevate the quality of data engineering across the organization.

  • Participate in an on-call rotation for support during and after business hours.

  • Lead design sessions and code reviews to elevate the quality of data engineering across the organization.


  • 8+ years of experience in Data Warehousing and development using data technologies such as Relational & NoSQL databases, open data formats, building data pipelines (ETL and ELT) with batch or streaming ingestion, loading and transforming data.

  • Expert in SQL and/or SQL based languages and performance tuning of SQL queries

  • Strong understanding of Normalized/Dimensional model disciplines and similar data warehousing techniques.

  • Strong experience working with ETL/ELT concepts of data integration, consolidation, enrichment, and aggregation in petabyte scale data sets.

  • Experience with at least one of the following cloud platforms: Microsoft Azure (Preferred), Amazon Web Services (AWS), or Google Cloud Platform (GCP)

  • Strong Experience with cloud-based data warehouses – e.g. Snowflake, BigQuery, Synapse, RedShift, etc.

  • Experience with message queuing, stream processing (Kafka, Flink, Spark Streams)

  • Strong Grasp of data management principles: Data Lake, Data Mesh, Data Catalog, Master Data, Data Quality, etc.

  • Experience in BI tooling such as Qlik, MicroStrategy, Tableau, PowerBI or Looker

  • Experience with orchestration tools (Control-M, Airflow etc)

  • Strong communication skills across different mediums to craft compelling messages to drive action and alignment.

  • Comfort with agile delivery methodologies in a fast-paced complex environment – Scrum, SAFe, utilizing tools such as Jira, Confluence, and GitHub

  • Ideal candidates will have experience working with one of the following industries: Retail, Supply Chain, Logistics, Manufacturing or Marketing

  • Proficient in Linux/Unix environments


Targeted Pay Range: $83,000 – $138,200. This is part of a competitive total rewards package that could include other components such as: incentive, equity and benefits. Individual pay is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all teammate pay regularly to ensure competitive and equitable pay.