Senior Backend Engineer, Data Platform
LaunchDarklyBase Salary
$158k - $257k/yr
Responsibilities
- Design, build, and operate distributed, data-intensive backend systems for Data Platform capabilities across Experimentation, Metrics, Release Guardian, Observability, Agent Control, and other product areas.
- Own and improve streaming and batch pipelines, analytical data stores, warehouse export systems, observability, alerting, reliability, and performance.
- Debug and resolve production issues across data pipelines, databases, cloud infrastructure, and distributed systems, including participation in the on-call rotation.
- Partner with product managers, frontend engineers, UX designers, and product engineering teams to deliver reliable customer-facing data capabilities.
- Write technical proposals, contribute to architecture decisions, and make trade-offs involving scalability, reliability, cost, and operability.
- Improve engineering standards, testing practices, deployment safety, observability, tooling, and operational processes.
- Write maintainable, well-tested code and participate in code reviews, design reviews, and production readiness discussions.
Requirements
- At least 6 years of professional backend software engineering experience, including significant experience with infrastructure, data platforms, distributed systems, or data-intensive production systems.
- Experience designing, building, operating, and debugging reliable production systems that move, store, process, or query large volumes of data.
- Hands-on experience with data pipeline, streaming, orchestration, or batch-processing technologies such as Kinesis, Airflow, Spark, Lambda, Flink, Athena, Kafka, or equivalent systems.
- Experience with analytical, event, warehouse, or operational data stores such as ClickHouse, Postgres, Elasticsearch, Timestream, Glue/Iceberg/S3, Redshift, Databricks, or equivalent systems.
- Strong programming experience in Go, Python, SQL, Scala, or similar backend languages.
- Familiarity with distributed systems and backend fundamentals including concurrency, data modeling, failure handling, retries, idempotency, partitioning, backpressure, and high-throughput processing.
- Experience with infrastructure-as-code tools such as Terraform and observability tools such as Datadog, New Relic, or equivalent.
- Strong ownership of production systems, including maintainability, testing, operational excellence, code quality, collaboration, and clear technical communication.
Benefits
- Restricted Stock Units (RSUs)
- Health, vision, and dental insurance
- Mental health benefits
Tech Stack
About LaunchDarkly
LaunchDarkly is the runtime control layer for the AI era. For over a decade we have helped engineering teams control what ships in production, starting with feature management and evolving into the infrastructure that governs how software and AI agents behave after deploy. With CodeControl and AgentControl, teams can update agent behavior in milliseconds, automatically roll back when something drifts, and govern every agent and feature across the organization from one place. No redeploys required. LaunchDarkly processes more than 50 trillion flag evaluations per day and serves some of the most demanding engineering teams in the world, including over a quarter of the Fortune 500. Founded in 2014 in Oakland, California by Edith Harbaugh and John Kodumal, LaunchDarkly has been named to the Forbes Cloud 100 for five consecutive years, Fast Company's Most Innovative Companies list, and the Inc. 5000.