Senior Backend Engineer, Data Platform

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.

Qualifications

• 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.

Compensation

Target pay ranges based on Geographic Zones* for Level 4:

• Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $187,000 - $257,000
• Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $168,000 - $231,000
• Zone 3: All other US locations - $158,000 - $218,000

*Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary.