Senior Data Engineer - Privacy & Governance
The National Basketball Association
SUMMARY The Senior Data Engineer will join our small, high-leverage data team building the data and intelligence platform for Pacers Sports & Entertainment (PS&E). This is a modern full-stack data & analytics engineering role spanning data modeling, pipeline development, and the user-facing applications that put data in front of decision-makers. The role works across the entire surface from raw ingestion through governed consumption layers and into the products that stakeholders actively use. AI-assisted development is core to how our team operates, not a side experiment. The successful candidate will contribute to a team culture where engineers move fluidly across the full data and application stack and leverage modern tooling to punch above their weight. This role carries a privacy and governance specialty. The successful candidate will own the PII classification model, access controls, and the technical systems that enforce how fan data is protected across the platform, upstream sources, and downstream activation partners. This is not a policy or compliance role; it is an engineering role that happens to specialize in privacy. ESSENTIAL DUTIES / RESPONSIBILITIES
- Design and maintain the enterprise PII classification model and the data catalog that maps where consumer data lives across sources, pipelines, and consumption layers.
- Implement Unity Catalog access controls including column masking, permission tiers, and the governance model that scales as the team and consumer base grow.
- Design and implement consent infrastructure including how opt-in and opt-out propagates from OneTrust through CRM, Marketing Cloud, and out to identity resolution and ad activation partners.
- Build and maintain privacy request execution flows that satisfy state-level regulations including CCPA, CPRA, and the broader patchwork of US privacy law.
- Document and audit vendor data flows including identity resolution and downstream activation partners.
- Build and maintain pipelines that move data from source systems through the medallion architecture in Databricks, including ingestion, transformation, and curation.
- Partner with stakeholders across the business to translate their questions and needs into well-modeled, well-documented, production-grade data products.
- Develop frontend or modern BI components for internal data products and analytics applications delivered by the team.
- Participate in code review, testing, and engineering standards alongside the rest of the team.
- Leverage AI-assisted coding tools to ship higher-quality work faster across the full stack.
- 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 while actively participating in company-sponsored community outreach programs.
- Other duties as assigned.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
- Five or more years building data systems in production environments.
- 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).
- Working knowledge of state, national and international privacy regulations (CCPA, CPRA, GDPR, etc.) and the technical patterns that satisfy them, approached from an engineering perspective rather than a legal one.
- Experience with consent management platforms such as OneTrust, identity resolution architectures, and the practical realities of vendor data flows in marketing and advertising technology.
- 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.
- Familiarity with agentic AI patterns and production experience using AI coding assistants such as Claude Code, Cursor, or similar tools.
- 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 requirements into concrete engineering decisions, balancing quality, stakeholder needs, and delivery speed.
- Making architectural and modeling decisions independently while knowing when to consult the team.
- Debugging issues across the full stack from raw source data through transformation logic into user-facing products.
- Investigating root causes rather than symptoms, with a bias toward shipping working software over perfect specifications.
Vacancy posted 4 days ago
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