Senior Manager, Software Engineering

<h2>Job Description: Senior Manager Software Engineering,</h2><h2>Data Foundation &amp; AI Data Access</h2><p></p><p><b>Summary</b></p><p><span>The Senior Engineering Manager, Data Foundation &amp; Data Access will lead the teams responsible for Rockerbox’s core data platform, data ingress, datalake adoption, APIs, permissions, and customer-facing data access patterns.</span></p><p><span>This role owns the connection between foundational data systems and the application/API layers that make that data usable by internal teams, customers, and AI-enabled workflows.</span></p><p></p><p></p><h2>Responsibilities</h2><ul><li><p><span>Lead engineering teams responsible for data ingress, pipelines, datalake adoption, Data APIs, permissions, and data access interfaces.</span></p></li><li><p><span>Own execution and technical direction across Rockerbox’s data foundation and customer-facing data access layers.</span></p></li><li><p><span>Ensure reliable, timely, and scalable client data delivery.</span></p></li><li><p><span>Align ingestion, aggregation, API access, permissions, and AI-enabled data workflows under clear ownership.</span></p></li><li><p><span>Partner with Product, Applications, Integrations, Data Science, Customer Success, and DV stakeholders on platform strategy.</span></p></li><li><p><span>Enable internal teams and customers to access Rockerbox data through APIs, CLI tooling, and future agentic workflows.</span></p></li><li><p><span>Improve team efficiency through automation, reduced maintenance burden, and clearer ownership.</span></p></li><li><p><span>Manage, develop, and retain engineers through a period of organizational transition.</span></p></li><li><p><span>Reduce bottlenecks between Data, Applications, and customer-facing product development.</span></p></li></ul><p></p><p></p><h2>Required Qualifications</h2><ul><li><p><span>Experience managing engineering teams responsible for data platforms, pipelines, APIs, or infrastructure.</span></p></li><li><p><span>Strong technical judgment across data architecture, data reliability, and application-facing access patterns.</span></p></li><li><p><span>Proven ability to lead cross-functional initiatives across Engineering, Product, Data Science, and Customer Success.</span></p></li><li><p><span>Track record of delivering platform improvements with measurable business impact.</span></p></li><li><p><span>Ability to operate at broader organizational scope beyond a single functional team.</span></p></li><li><p><span>Strong people leadership, communication, and execution skills.</span></p></li></ul><p></p><p></p><h2>Preferred Qualifications</h2><ul><li><p><span>Experience with datalake or warehouse adoption across multiple teams.</span></p></li><li><p><span>Experience building Data APIs, permissions systems, or customer-facing data access layers.</span></p></li><li><p><span>Experience with AI-enabled workflows, LLM tooling, or agentic data access patterns.</span></p></li><li><p><span>Experience reducing operational load through automation.</span></p></li><li><p><span>Familiarity with marketing analytics, MTA, MMM, testing, and customer data platforms.</span></p></li></ul><p></p><p></p><h2>Success Measures</h2><ul><li><p><span>Clear ownership across Data, APIs, permissions, and customer-facing access.</span></p></li><li><p><span>Reliable and timely client data delivery.</span></p></li><li><p><span>Faster execution on AI-enabling Data API initiatives.</span></p></li><li><p><span>Broader datalake adoption across internal teams.</span></p></li><li><p><span>Reduced dependency bottlenecks between Data and Applications.</span></p></li><li><p><span>Improved engineering capacity through automation.</span></p></li><li><p><span>Strong retention and development of critical engineering talent.</span></p></li></ul><p><br>&nbsp;</p>