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Salary: USD 163,000 - 263,670 / annual
LaunchDarkly is seeking an Engineering Manager to lead the Data Platform team, responsible for the high-throughput data backbone powering Experimentation, Metrics, Observability, Release Guardian, AgentControl, and Data Export. You will lead a technically deep team building and operating systems that ingest, process, and serve real-time and batch data at scale.
The team works primarily in Go and Python, tackling distributed-systems challenges using Kinesis, Airflow, Athena, Iceberg on S3, ClickHouse, Elasticsearch, Terraform, AWS, and Datadog. You'll guide the platform that transforms vast volumes of events into reliable, customer-facing product experiences while partnering across Core Engineering and product teams.
Key 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 downstream pipelines and data stores
- Partner with Product Management and consuming engineering teams to scope, estimate, and sequence roadmap work, making real-time tradeoffs
- 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 software engineering experience, 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 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
