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Senior Backend Engineer, Data Platform

πŸ•’ 21 days ago
Backend EngineeringDistributed SystemsData InfrastructureStreaming Technologies

πŸ“œ Description

  • 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.

πŸ› οΈ 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.
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