Senior Data Engineer - Athlete (REMOTE)

DICK'S Sporting Goods

1d•$83,000 - $138,200•Remote

About The Position

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: On the Athlete Data team, we build the data foundation that powers personalized customer experiences, loyalty programs, and marketing insights. Our work spans multiple systems and partners, and—just like all great teams—it requires trust, clarity, discipline, and collaboration. We’re looking for a Senior Data Engineer who values thoughtful problem‑solving, clean design, and strong data hygiene. Someone who can move between conceptual modeling and hands‑on implementation, and who enjoys working in an environment where everyone succeeds through the strengths they bring to the team. Capable engineers thrive here because we emphasize transparency, respect, steady improvement, and shared wins. Job Purpose: As a Senior Data Engineer on the Athlete team, you’ll work across a diverse and evolving data ecosystem that supports critical marketing functions. The role requires the ability to operate both deep within complex data domains and broadly across many systems, partners, and vendors. You’ll turn loosely defined business problems into clear, executable data solutions, helping bring structure and momentum to ambiguous work. You’ll play a key role in designing, building, and evolving data pipelines and models—especially in environments that involve sensitive customer data, identity resolution, and the unification of disparate sources. Success in this role depends on strong technical fundamentals, sound data judgment, and the ability to collaborate effectively across analytics, engineering, marketing, and product teams.

Requirements

Strong SQL and Python fundamentals
Experience with Databricks/Spark or similar large‑scale platforms
Clarity in thinking about data models and transformations
Detail‑orientated and disciplined data hygiene
Ability to break down complex problems and communicate them clearly
Team-first mindset — you share, collaborate, and elevate others

Nice To Haves

Experience in refactoring codebase, cataloging/data governance, and agile development are a plus
Curiosity and willingness to learn new tools/contexts quickly

Responsibilities

Build High‑Quality Pipelines Develop reliable data pipelines using SQL, Python, Databricks/Spark.
Improve and modernize existing pipelines for clarity, performance, and maintainability.
Add tests, documentation, lineage, and observability to strengthen trust.
Model Data Across Many Systems Translate complex, multi‑source schemas into clear conceptual and physical models.
Handle grain alignment, key logic, and definition clarity with care.
Design models that scale and reduce friction for analysts, product, and downstream users.
Protect Customer Data Apply disciplined data hygiene and privacy-first patterns.
Safely move and store sensitive customer data in compliance with organizational standards.
Collaborate Across the Field Partner with analysts, product managers, marketing teams, data scientists, vendor teams, and other engineers.
Communicate assumptions, trade‑offs, and decision points clearly.
Bring clarity to ambiguous problems and help guide the team toward the best path forward.
Lift the Team Like any high-performing team, we win together: Share knowledge, document meaningfully, and help strengthen team patterns.
Support teammates through code reviews, pairing, and problem‑solving.
Use AI‑assisted tools to accelerate documentation, test generation, and iteration.