Senior Data Engineer (REMOTE)

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!

OVERVIEW:

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 to make us even stronger. In this role, you will build dataset and make it accessible to our partner teams by writing great code to simplify the complexity and ensure quality. Your work will enable product teams, data scientists, and decision-makers across the company to bring together insights and inform our business.

We believe that trusted, easy to consume data is critical and as a Senior Data Engineer your work will help to build that foundation.

You will also be responsible for the daily operations inclusive of troubleshooting and job monitoring.  You will be a part of the growing Data team reporting to the Sr. Director, Data Analytics.

 The impact you will have:

Design/Strategy: You will design and support the business’s database and table schemas for new and existing data sources for the data warehouse. Creates and supports the ETL to facilitate data accommodation into the warehouse. In this capacity, the Data Engineer designs and develops systems for the maintenance of the business’s data warehouse, ETL processes, and business intelligence.

Collaboration: You will be collaborative - working closely with analysts, data scientists, and other data consumers within the business to gather and deliver high quality data for business cases. The Data Engineer also works closely with other disciplines/departments and teams across the business in coming up with simple, functional, and elegant solutions that balance data needs across the business

Analytics: You will play an analytical role in quickly and thoroughly analyzing business requirements and subsequently translating the emanating results into good technical data designs. In this capacity, the Data Engineer establishes the documentation of the data solutions, develops, and maintains technical specification documentation for all reports and processes.

What You Will Do

• You’ll be working with a variety of internal teams -- Engineering, Business -- to help them solve their data needs

• Your work will provide teams with visibility into how DICKs products are being used and how we can better serve our customers

• Identify data needs for business and product teams, understand their specific requirements for metrics and analysis, and build efficient and scalable data pipelines to enable data-driven decisions across DICKs.

• Experience in one or more of the following: Python (Preferred), Scala, C++, or Java.

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

• Help the Data Analytics & Data Science team apply and generalize statistical and econometric models on large datasets

• Drive the collection of new data and the refinement of existing data sources, develop relationships with production engineering teams to manage our data structures as the DICKs product evolves

• Develop strong subject matter expertise and manage the SLAs for those data pipelines

• 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.

Technical Skills

• 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.

• Experience in one or more of the programming languages are required: Python (Preferred), Scala, C++, or Java, Go, Kotlin.

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

• Experienced with ETL/ELT in Databricks, with Medallion architecture and with Delta Lake, Unity Catalog, Delta Sharing, Delta Live Tables (DLT).

• Experience with CI/CD on Databricks using tools such as GitHub Actions, and Databricks CLI.

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

QUALIFICATIONS:

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