Engineering Manager

• Lead, coach and grow a team responsible for data ingestion, transformations, integration connectors, and data warehouse.
• Be a hands-on manager: split time between people management and technical work (architecture, code reviews, system design, and occasionally shipping code yourself).
• Own delivery and outcomes for pipeline/integration and data warehouse projects. Set priorities with Product, remove blockers, and protect engineering focus.
• Design and evolve reliable, observable, and secure data pipelines, data schemas, and integrations.
• Drive best practices for data quality, schema evolution, idempotency, retries, backfills, and monitoring/alerting.
• Collaborate with AI focused teams and Platform teams to design data contracts and interfaces that enable analytics and AI experiences (feature stores, embeddings, semantic indices).
• Make architectural decisions with an eye toward scale, operability, cost, and maintainability; partner closely with Staff engineers on long-term architectural work.
• Recruit, mentor, and develop engineers, helping them grow technically and in their careers.
• Establish SLOs/SLIs for pipeline reliability, latency, and throughput; lead team incident response measures and postmortems.

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