Senior Product Software Engineer - Data Platform

Senior Product Software Engineer - Data Platform Job Summary

We’re hiring Innovative Data Platform Automation Engineer to cut manual toil and raise reliability across our data platform—through better monitoring and the tools that support it. In this role you will design and build services and internal tooling that keep production data pipelines healthy, with a strong focus on automating monitoring, speeding up pipeline debugging, and maintaining SLAs. You will also help develop AI agents and workflows that assist with debugging complex pipelines by connecting runtime signals to our knowledge base, and that work with data quality services to surface, explain, and triage data issues faster.

• Automate recurring operational work — convert runbooks and ad-hoc fixes into version-controlled automation (Python/Go CLIs, scheduled jobs, CI-driven checks, or lightweight services) and traceable execution.
• Partner with data engineers on the real system — model DAG dependencies, SLAs/SLO touchpoints, and orchestration.
• Prioritize tooling that accelerates incident response: dependency/lineage views, data freshness monitors, schema/drift checks.
• Build agentic workflows for faster isolation — implement LLM-assisted triage services that fuse metrics, logs/traces, orchestrator task metadata, data quality rules, and incident history with dependency-aware evaluations to propose ranked hypotheses and verification steps (e.g. partition gaps, late upstream, contention, bad deploy, contract mismatch).
• Integrate via webhooks/APIs into on-call workflows (Pager Duty/Slack/Jira) with guardrails.

• Bachelor’s degree in computer science, engineering, or related technical field (Master’s preferred), or equivalent experience.
• 5+ years in data platform engineering, or data operations (Data Ops/SRE-style), with demonstrable experience shipping AI-assisted automation and internal tool expertise.
• Strong Python: application/library development, testing (unit/integration), packaging and distribution, and production-minded practices (logging, config, error handling, observability hooks as appropriate).
• APIs and integration experience: experience building HTTP/gRPC services, internal SDKs/CLIs, or platform components consumed by multiple teams.
• LLM engineering: hands‑on use of LLM APIs (e.g., OpenAI, Anthropic) and orchestration with frameworks such as Lang Chain or Lang Graph (or equivalent), including prompt/tool design, evaluation, and safe production patterns (permissions, guardrails, cost/latency controls).
• Agentic systems in practice: shipped reusable agents, workflows, or libraries that improved debugging, triage, or automation—and were adopted beyond a single team.
• Cross-functional execution: strong communication and stakeholder management across infrastructure, data engineering, security, and product; comfortable translating ambiguous operational pain into measurable platform outcomes.

• Strong software engineering experience to build tools and services with Python or GoLang.
• Understanding of data platform such as Databricks, Snowflake and ETL tools such as Spark.
• Previous experience in a developer enablement role (platform engineering, frameworks, SDKs) where reusable components accelerated adoption across large organizations.

The hiring range for this position in Los Angeles, California is $141,900 to $190,300 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.