Engineering Manager, Warehouse Scale

We're looking for an engineering manager for our Warehouse Scale team. In this role, you'll lead the team that builds and operates the foundational data infrastructure powering LaunchDarkly's warehouse-native products — data export pipelines, warehouse health checks, and warehouse connection setup.

You'll bring a balance of people management and technical leadership as you drive the development of critical platform infrastructure and foster a high-performing, collaborative engineering culture. You'll partner closely with Product Management and cross-functional teams to deliver reliable, scalable systems that enterprise customers depend on.

Responsibilities:

Lead and develop a team of backend engineers, providing coaching, feedback, and career growth opportunities

Partner with PM and Design to scope, estimate, and sequence roadmap items, making scope tradeoffs in real time

Own the team's delivery of critical infrastructure — data export pipelines, DAG orchestration, warehouse health checks, and connection setup

Collaborate with adjacent teams (Warehouse Integrations, Experimentation, Data Platform) on shared infrastructure decisions and cross-team dependencies

Communicate roadmaps, risks, and progress clearly to engineering leadership and cross-functional stakeholders

Build team working norms that promote collaboration, reduce silos, and keep engineers engaged

Drive operational excellence — improve reliability, observability, and incident response for production data infrastructure

Participate in hiring to grow the team and raise the engineering bar

Qualifications:

3+ years of experience in software engineering, with at least 2 years managing a team of backend or infrastructure engineers

Experience building or operating data infrastructure at scale — pipelines, orchestration frameworks, or data platform systems

Proven ability to partner with Product Management to translate business goals into engineering plans with reliable estimations

Strong communication skills, especially in distributed team environments with cross-timezone collaboration