Engineering Manager (Data Platform)

About the role

Join LaunchDarkly as an Engineering Manager for the Data Platform team. In this role, you will lead a technically deep team responsible for building and operating the systems that ingest, process, and serve real-time and batch data. You will work primarily in Go and Python and tackle ambitious distributed-systems challenges. You will also be responsible for the delivery, correctness, and resilience of the Data Platform's production systems, and will partner with Product Management and other engineering teams to scope and estimate roadmap work. Additionally, you will drive operational excellence and build team working norms that promote collaboration and engagement. Key missions: 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. Profile: - Experience with Go or Python, and with technologies such as Kafka or Kinesis, ClickHouse, Airflow, Athena or Iceberg, Elasticsearch, and Terraform is a plus - Familiarity with observability practices (metrics, tracing, alerting, structured logging) and comfort leading production incident response - 8+ years of experience in software engineering, with at least 2 years managing a team of backend or infrastructure engineers - 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 - Strong communication skills in a distributed, cross-time-zone environment - Track record of coaching and developing engineers, including performance management, career growth planning, and technical mentorship - Experience owning high-throughput, reliability-critical production systems such as event ingestion, streaming or batch pipelines, or large analytical data stores