Engineering Manager, Data Platform

Role overview Lead the Data Platform team that builds and operates the high-throughput, real-time and batch data backbone powering experimentation, metrics, observability, release safety, agent control, and data export products. The role centers on guiding distributed-systems engineering in Go and Python across streaming and analytical systems, partnering closely with product management and consuming engineering teams to make data faster, more resilient, and more useful for every customer. It combines deep technical judgment with people leadership for a globally distributed organization.

Responsibilities - Lead and develop a team of backend engineers, providing coaching, feedback, and structured career growth opportunities. - Own delivery, correctness, and resilience of Data Platform production systems, including Tier 0 ingestion endpoints and the pipelines and stores behind them. - Partner with Product Management and consuming engineering teams to scope, estimate, and sequence roadmap work, making trade-offs in real time. - Serve as the primary communicator and point of contact for Data Platform across engineering leadership, partner teams, and customers. - Drive operational excellence across reliability, observability, cost, incident response, and on-call health. - Build team working norms that reduce silos and bus factor, foster collaboration, and keep engineers engaged. - Participate in hiring to grow the team and raise the engineering bar.

Requirements - 8+ years of software engineering experience, with at least 2 years managing a team of backend or infrastructure engineers. - Experience owning high-throughput, reliability-critical production systems such as event ingestion, streaming or batch pipelines, or large analytical data stores. - Strong distributed-systems fundamentals and the judgment to guide technical trade-offs with senior engineers. - Proven ability to partner with Product Management to translate business goals into engineering plans with reliable estimates. - Track record of coaching and developing engineers, including performance management and technical mentorship. - Strong communication skills in a distributed, cross-time-zone environment. - Familiarity with observability practices (metrics, tracing, alerting, structured logging) and comfort leading incident response.

Nice to have - Hands-on experience with Go or Python, and with technologies such as Kafka or Kinesis, ClickHouse, Airflow, Athena or Iceberg, Elasticsearch, and Terraform.

Benefits and work setup - Published geographic pay zones for US locations, inclusive of a 10% bonus target, with the example range $163,000–$224,070 USD for Zone 3, plus restricted stock units, health, vision, dental, and mental health benefits.