Lead, Solutions Architect - Data Analytics Engineering
At Under Armour, we are committed to empowering those who strive for more. Our values—Act Sustainably, Celebrate the Wins, Fight on Together, Love Athletes, and Stand for Equality—serve as a roadmap for our teams and the qualities expected of every teammate. These values define and unite us, connecting everyone at Under Armour and fueling everything we do. Our pursuit of better begins with innovation and a mission to be the best, offering the freedom to go further in developing, delivering, and selling state-of-the-art products and digital tools that enhance performance.
Purpose of Role
Under Armour is seeking a seasoned Lead Solutions Architect, Data Analytics Engineering, to govern and deliver modern data and analytics platforms that power strategic decision-making across the organization. This role serves as a technical lead within EDMA, responsible for architecting enterprise-scale data products, defining engineering and modeling standards, and driving modernization across the Data Analytics/Decision Products ecosystem. The role leads complex cross-functional programs, establishes Data Engineering best practices, and partners closely with Data Engineering, Automation & AI, Analysts, and Data Governance leadership to shape the roadmap and technical direction.
Responsibilities
- Enterprise Data Architecture & Engineering Leadership
- Design and govern scalable ELT architectures, including advanced dbt modeling frameworks.
- Lead the development of large, complex data pipelines, automation workflows, and decision intelligence solutions.
- Own the end-to-end lifecycle of enterprise-grade decision products used across functions.
- Define and enforce architecture standards, modeling patterns, semantic layer principles, and engineering best practices.
- Drive data platform modernization efforts, including migration, optimization, and adoption of emerging technologies.
- Snowflake & Data Platform Excellence
- Serve as the technical authority on Snowflake performance tuning, VWH optimization, RBAC frameworks, query efficiency, and cost engineering.
- Lead modeling patterns, data sharing strategies, and enterprise semantic layer design.
- Quality, CI/CD & Operational Reliability
- Own significant components of the CI/CD pipeline, ensuring high reliability, automated testing, and governance.
- Establish DataOps best practices across squads, including observability, monitoring, alerting, and versioning standards.
- Oversee release management, change management processes, and production stability for decision products.
- Leadership, Mentorship & Cross-Functional Influence
- Mentor junior-level engineers; drive engineering maturity through code reviews, design reviews, and technical coaching.
- Facilitate complex stakeholder sessions to align business requirements, architecture decisions, and delivery plans.
- Lead cross-functional data programs spanning Product, Platform, Automation, AI, Governance, and Analytics.
- Partner with Product & Engineering leadership to shape roadmap priorities, standards, and long-term technical vision.
- Deliver executive-level presentations on architecture decisions, design tradeoffs, and product strategies.
- Automation & AI Enablement
- Build or integrate advanced automation frameworks supporting high-scale operational workflows.
- Apply Generative AI to streamline development, improve design standards, and scale repeatable engineering patterns.
Requirements
- Expert SQL abilities with mastery in complex data transformation and optimization techniques.
- Deep expertise in data modeling, ELT architecture, and enterprise data ecosystems.
- Proven ability to design and lead scalable data apps, automation pipelines, and decision intelligence solutions.
- Strong proficiency with Tableau or similar analytics platforms.
- Production-level dbt expertise (modularity, testing, documentation, governance).
- Strong background in CI/CD engineering, release management, and DevOps integration.
- Advanced Snowflake engineering skills: VWH tuning, RBAC, cost/performance engineering, workload optimization, semantic layer design.
- Advanced Python for automation, orchestration, and workflow engineering.
- Experience with automation platforms such as Elementum.
- Strong architectural influence, cross-functional communication, and engineering leadership.
- Ability to leverage Generative AI tools responsibly to improve engineering productivity and design quality.
- Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, or related technical field.
- 7+ years in Data Engineering, Analytics Engineering, or Decision product development.
- 6+ years of Snowflake experience (VWH optimization, RBAC, cost/performance engineering, semantic layer design).
- 5+ years of experience in dbt or similar data transformation/data orchestration tools.
- 5+ years of experience with Tableau, Power BI, or similar analytics platforms.
- 5+ years of experience and strong background in CI/CD engineering best practices.
Preferred Qualifications
- Professional dbt/Snowflake certifications.
- SAP ERP domain knowledge.
Workplace Location
This individual must reside within commuting distance from our Baltimore HQ office. Candidates must reside within a commutable distance to our corporate headquarters in Baltimore, Maryland, as periodic on-site attendance may be required. Travel: 5% of the year.
Pay
Base Compensation: $125,000.00–$165,000.00 USD. Most new hires fall within this range and have the opportunity to earn more over time. Initial placement within the salary range is based on an individual's relevant knowledge, skills, and experience for the position.
Benefits
- Paid "UA Give Back" Volunteer Days: Work alongside your team to support initiatives in your local community.
- Under Armour Merchandise Discounts.
- Competitive 401(k) plan matching.
- Maternity and Parental Leave for eligible and FMLA-eligible teammates.
- Health & fitness benefits, discounts, and resources to promote physical activity and overall well-being.