Solution Architect - Data (REMOTE)

DICK'S Sporting Goods

2d • 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: Our company is looking to invest in our future as we embark on a journey from being the best sports retailer in the world to becoming the best sports company in the world. We’re building an unrivaled and agile inventory ecosystem fueled by predictive insights, operational excellence, strategic partnerships, and empowered teams. Our goal: deliver the right product to the right place at the right time—every time. If you’re passionate about innovation, data, and making a tangible impact, Inventory360 is where you can help lead the future of retail. Are you a curious, analytically minded technologist who thrives on turning ambiguous business problems into clear, data-driven answers? This is an opportunity to sit at the intersection of data strategy, business intelligence, and architecture for a leading sports retailer with $14B+ in revenue and 800+ physical stores. At DICK'S Sporting Goods, we put our Athletes (customers) and Teammates (employees) at the center of every decision. That means building a deep understanding of who they are, what they need, and how data can serve them better — across every channel, every touchpoint, and every moment that matters. When you join our Technology team, you join a team that wins together. About the Role This is not a purely technical architecture role. The Solution Architect – Data is a hybrid practitioner: part data architect, part analyst, part discovery lead. You will be the connective tissue between business stakeholders and data engineering — someone who can walk into a room with a VP of Merchandising or a Loyalty team and help them articulate not just what they want to build, but what questions they are truly trying to answer with their data. You will lead discovery and requirements workshops, translate business intent into actionable data requirements, analyze data to validate hypotheses and surface insights, and produce the documentation and artifacts that allow engineering teams to build with confidence. Data architecture is part of your toolkit — but your greatest leverage is your ability to make data meaningful to the people who use it.

Requirements

• 7–10 years of experience spanning data engineering, analytics, and/or solution architecture
• Demonstrated ability to lead discovery sessions and translate business problems into data requirements — asking "what question are you trying to answer?" before reaching for a tool
• Strong hands-on SQL and Python skills; you are comfortable getting into the data yourself
• Experience with customer and loyalty data in a retail or omnichannel commerce context
• Comfort working across behavioral, transactional, and operational datasets at enterprise scale
• Excellent written and verbal communication — creating artifacts and documentation that are clear, practical, and widely adopted by teams
• Experience with cloud-based data platforms and modern data architecture patterns (Medallion architecture, Data Mesh concepts, Data Catalog, Data Quality frameworks)
• Ability to hold a room: facilitating workshops, presenting findings, and influencing without authority
• Bachelor's degree in Computer Science, Information Systems or related field required.

Nice To Haves

• Fatai
• Google BigQuery
• Cloud-native platform concepts (Kubernetes, containerization, distributed systems)

Responsibilities

• Discovery & Requirements Lead business stakeholder workshops to surface data needs, refine use cases, and drive ambiguous asks toward precise, answerable questions
• Partner with Product to challenge, sharpen, and validate requirements before engineering investment begins
• Translate business outcomes — loyalty, customer lifetime value, athlete behavior, in-store and digital performance — into data requirements and analytical framings
• Identify gaps between what data exists, what is accessible, and what the business needs to operate effectively
• Data Analysis & Insight Generation Analyze large, complex datasets across customer, transactional, behavioral, and operational domains to validate requirements, identify patterns, and inform solution design
• Develop and socialize analytical findings that directly influence product and platform decisions
• Support self-service data enablement by helping business users understand and interact with data assets more effectively
• Act as a thought partner on loyalty and customer data strategy, bringing a retail/CPG analytics lens to how we understand athlete behavior across channels
• Documentation & Artifacts Produce clear, professional artifacts including current and future state data flows, domain data models, source-to-target mappings, data dictionaries, and decision records
• Document data lineage, governance considerations, and integration patterns in a way that is accessible to both technical and non-technical audiences
• Maintain discovery outputs — workshop notes, requirement briefs, use case trackers — that keep stakeholders and engineering aligned through delivery
• Data Architecture Apply data architecture principles to evaluate, design, and recommend solutions across our cloud data platforms
• Contribute to enterprise data model standards, integration patterns, and platform decisions in partnership with engineering and foundational tech teams
• Assess data quality, lineage, and governance implications of proposed solutions
• Ensure designs account for scalability, reliability, and cost — without over-engineering for the problem at hand

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level