Senior Backend Engineer, Data Platform

LaunchDarkly is a company that empowers teams to deliver and control software safely. As a Senior Backend Engineer on the Data Platform team, you will build and operate the distributed data infrastructure that supports large volumes of product data, ensuring reliability and performance across various product capabilities.

Responsibilities:

• Design, build, and operate distributed, data-intensive backend systems that power Data Platform capabilities across Experimentation, Metrics, Release Guardian, Observability, Agent Control, and other product areas
• Own and improve production data infrastructure, including streaming and batch pipelines, analytical data stores, warehouse export systems, observability, alerting, reliability, and performance
• Debug and resolve complex production issues across data pipelines, databases, cloud infrastructure, and distributed systems, including participating in the team’s on-call rotation
• Partner with product managers, frontend engineers, UX designers, and other product engineering teams to deliver reliable customer-facing data capabilities
• Write and review technical proposals, contribute to architecture decisions, and help the team make thoughtful trade-offs around scalability, reliability, cost, and operability
• Improve engineering standards, testing practices, deployment safety, observability, tooling, and operational processes for Data Platform systems
• Write maintainable, well-tested code and actively participate in code reviews, design reviews, and production readiness discussions

Requirements:

• 6+ years of professional backend software engineering experience, including significant experience with infrastructure, data platform, 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 working 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 engineering fundamentals such as concurrency, data modeling, failure handling, retries, idempotency, partitioning, backpressure, and high-throughput processing
• Experience with infrastructure-as-code tools such as Terraform or equivalent, and observability tools such as Datadog, New Relic, or equivalent
• A strong ownership mindset for production systems, including maintainability, testing, operational excellence, code quality, collaboration, and clear technical communication