Engineering Manager, Data Platform

LaunchDarkly provides a software delivery platform that helps developers release, experiment with, and manage application features safely. The Engineering Manager will lead the Data Platform team, overseeing high-throughput systems that ingest, process, and serve real-time and batch data while driving reliability, operational excellence, roadmap execution, and team development.

Responsibilities:

• Lead and develop a team of backend engineers, providing coaching, feedback, and career growth opportunities
• Own the delivery, correctness, and resilience of Data Platform's production systems, including Tier 0 ingestion endpoints and the pipelines and data stores behind them
• Partner with Product Management and consuming engineering teams to scope, estimate, and sequence roadmap work, making tradeoffs in real time
• Act as the primary communicator and point of contact for Data Platform with engineering leadership, partner teams, and customers
• Drive operational excellence: reliability, observability, cost, incident response, and on-call health
• Build team working norms that promote collaboration, reduce silos and bus factor, and keep engineers engaged
• Participate in hiring to grow the team and raise the engineering bar

Requirements:

• 8+ years of experience in software engineering, with at least 2 years managing a team of backend or infrastructure engineers
• Experience owning high-throughput, reliability-critical production systems such as event ingestion, streaming or batch pipelines, or large analytical data stores
• Strong distributed-systems fundamentals and the judgment to guide technical tradeoffs with senior engineers
• Proven ability to partner with Product Management to translate business goals into engineering plans with reliable estimates
• Track record of coaching and developing engineers, including performance management, career growth planning, and technical mentorship
• Strong communication skills in a distributed, cross-time-zone environment
• Familiarity with observability practices (metrics, tracing, alerting, structured logging) and comfort leading production incident response
• Experience with Go or Python, and with technologies such as Kafka or Kinesis, ClickHouse, Airflow, Athena or Iceberg, Elasticsearch, and Terraform is a plus