Data Architect
AEG Presents
In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow-up screen. SUMMARY The Data Architect is a builder-architect: the person who writes the code, sets the patterns, and makes the hard tradeoffs that shape the platform the rest of the team builds on. This is a modern full-stack data & analytics engineering role with hands-on technical leadership, not a paper architect role. The successful candidate will own platform architecture, data modeling, governance standards, and the long-term technical direction of the data and intelligence platform for Pacers Sports & Entertainment. The role spans the entire surface from raw ingestion through governed consumption layers and into the experience layer that stakeholders actively use, including designing a platform that LLM-powered applications can consume natively. This role ships the reference implementation before anyone else, writes the patterns the rest of the team follows, and makes today's decisions with two years of capability growth in mind. ESSENTIAL DUTIES / RESPONSIBILITIES
Platform Architecture
Platform Architecture
- Own the design and evolution of the lakehouse architecture in Databricks, including medallion layer boundaries, compute and storage strategy, and catalog structure.
- Build and maintain the foundational platform components that everything else runs on, proving the architecture with working code before handing patterns to the team.
- Design and build the consumption layer patterns that govern how gold layer datasets get served through frontends, BI tools, APIs, and LLM-powered interfaces.
- Define the data access and retrieval patterns that enable LLM-powered applications to query the platform safely, including context retrieval, embedding strategies, and PII guardrails.
- Design and build canonical data records including the fan intelligence data store, identity resolution logic, and cross-property audience models.
- Own the semantic layer and metric catalog that governs how the business is represented in data, ensuring consistency across ticketing, partnerships, basketball operations, and corporate reporting.
- Define and implement data contracts, lineage tracking, access controls, and quality thresholds that keep the platform healthy as the team and consumer base scale.
- Design Unity Catalog governance including permission tiers, column masking for PII, and the access model that downstream consumers and privacy controls depend on.
- Own the platform roadmap and set the engineering patterns that the team adopts, establishing standards through example rather than documentation alone.
- Mentor engineers on data modeling, platform design, and architectural decision-making, raising the technical ceiling of the team.
- Make the hard tradeoffs between speed and durability, simplicity and flexibility, and communicate the reasoning clearly to engineering and leadership.
- Participate in a shared on-call rotation for production data systems, responding to incidents and contributing to postmortems and reliability improvements.
- In every position, each employee is expected to align with PS&E's mission and core values along with actively participating in company-sponsored community outreach programs.
- Other duties as assigned.
- Seven or more years building data systems in production environments, with progressive responsibility for platform design and data modeling.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Track record of designing and building a lakehouse or data warehouse through a messy-to-mature journey, not just operating one that was already well-architected.
- Hands-on experience with identity resolution, dimensional modeling, and semantic layer design that business users have adopted at scale.
- Experience setting engineering patterns and standards for a team, including code review practices, data contracts, and platform governance.
- Production experience in the consumption layer through either frontend web development (React, Next.js, or similar) or Analytics tools (Tableau, Power BI, Looker, Hex, or comparable).
- Strong Python and SQL, with hands-on cloud lakehouse experience; Databricks preferred.
- Production experience with dbt for transformation and modeling, and Airflow or comparable orchestration frameworks.
- Deep understanding of Unity Catalog, Delta Lake, and lakehouse governance patterns.
- Familiarity with agentic AI patterns and production experience using AI coding assistants such as Claude Code, Cursor, or similar tools.
- Understanding of how to design data platforms that LLM-powered applications can consume natively, including RAG architecture, context retrieval patterns, and PII guardrails for AI consumption.
- Comfort moving across the stack: building a pipeline, modeling a domain, writing a Python service, and standing up a simple web interface independently.
- Working knowledge of Azure cloud services, version control with Git, and CI/CD patterns.
- Translating ambiguous business and technical requirements into concrete architectural decisions, balancing quality, stakeholder needs, and delivery speed.
- Making hard tradeoffs between competing priorities and communicating the reasoning to both engineering peers and business leadership.
- Investigating root causes rather than symptoms, with a bias toward building durable solutions that prevent recurrence.
Vacancy posted 3 days ago
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