Data Platform Engineering Manager

LaunchDarkly; Oakland (CA); On-site; USD 192,000 - 264,000; Full time

Job summary

LaunchDarkly is seeking an Engineering Manager to lead the Data Platform team, shaping the high-throughput data backbone behind our main products. You’ll guide a technically deep group building and operating systems that ingest, process, and serve real-time and batch data powering experimentation, metrics, observability, and more.

Working primarily in Go and Python, you’ll tackle distributed-systems challenges using Kinesis, Airflow, Athena, and Iceberg on S3, ClickHouse, Elasticsearch,

Qualifications

• 8+ years in software engineering with leadership experience.
• Experience owning high-throughput, reliability-critical production systems.
• Strong distributed-systems fundamentals and ability to guide technical tradeoffs.
• Proven ability to partner with Product Management to translate business goals into engineering plans.

Responsibilities

• Lead and develop a team of backend engineers, providing coaching and growth opportunities.
• Own delivery, correctness, and resilience of Data Platform production systems.
• Collaborate with Product Management and consuming teams to scope and sequence roadmap work.
• Serve as primary communicator for Data Platform with engineering leadership and customers.
• Drive operational excellence: reliability, observability, cost, incident response, on-call health.
• Build norms that promote collaboration and reduce silos and bus factor.
• Participate in hiring to grow the team and raise the engineering bar.

Skills

Team leadership

Distributed systems

Go/Python

Production systems

Stakeholder collaboration

Hiring and mentoring

Tools

Go

Python

Kinesis

Airflow

Iceberg

Elasticsearch

Terraform

AWS

Datadog

Job description

LaunchDarkly is seeking an Engineering Manager to lead the Data Platform team, shaping the high-throughput data backbone behind our main products. You’ll guide a technically deep group building and operating systems that ingest, process, and serve real-time and batch data powering experimentation, metrics, observability, and more.

Working primarily in Go and Python, you’ll tackle distributed-systems challenges using Kinesis, Airflow, Athena, and Iceberg on S3, ClickHouse, Elasticsearch,