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# Software Engineer, Data Engineering

- **Company:** Roblox
- **Location:** San Mateo, CA, United States
- **Experience:** Expert
- **Salary:** $243,290 - $295,250
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Information Engineering, Data Systems, Programming Tools, Machine Learning, Metadata, DataOps, Software Engineering, Roblox
- **Published:** November 14, 2026
- **Apply:** https://careers.roblox.com/jobs/8366921?gh_jid=8366921

## About the Role

* Strong software engineering experience building and operating production systems, platforms, or developer tools.
 * Experience designing services or frameworks that are reused by multiple teams, with attention to reliability, maintainability, observability, and user experience.
 * Experience with data systems or operational workflows, for example, metadata, data quality, lineage, orchestration, monitoring, or large-scale pipeline operations.
 * Sound judgment for turning ambiguous problems into incremental, measurable solutions, and for balancing automation with appropriate safeguards.
 * Experience evaluating automated or AI-assisted systems using representative tests, measurable outcomes, and ongoing production feedback; familiarity with agentic workflows is especially relevant.
 * The ability to collaborate across engineering and data disciplines, influence technical decisions, and explain complex tradeoffs to varied audiences.
 * A track record of mentoring peers and raising engineering quality without relying on formal authority.

## Description

We are looking for a Senior Software Engineer to design, build, and operate high-leverage data tooling used across Roblox. You will own substantial technical work from problem discovery through production rollout, turning complex operational signals into clear, dependable workflows.

A key focus for this role is intelligent automation for data operations: helping people and systems discover relevant data, diagnose quality or pipeline issues, understand cost and lifecycle signals, and take safe next steps. You will build these capabilities with strong evaluation, observability, and human oversight.

You will

 * Design, implement, and operate shared services, frameworks, and developer experiences for data quality, lineage, metadata, ownership, observability, lifecycle management, and optimization.
 * Turn signals such as freshness, quality failures, lineage, usage, and compute or storage cost into actionable alerts, recommendations, dashboards, and workflows.
 * Build AI-assisted or agentic experiences that help users investigate data questions and operational issues, with appropriate permissions, traceability, safety checks, and human approval for consequential actions.
 * Develop evaluation infrastructure for automated recommendations and actions, including reproducible tests, measurable quality criteria, regression checks, and monitoring for failures or unintended behavior.
 * Improve how teams discover, validate, govern, and operate data products, reducing toil while preserving clear ownership and reliable controls.
 * Partner with Data Engineering, Data Science, Experimentation, ML, product, and infrastructure teams to understand needs and deliver reusable solutions rather than one-off fixes.
 * Own production readiness for your work: instrumentation, service health, rollout plans, incident response, and follow-through on reliability and usability improvements.
 * Lead technical design for projects or workstreams, communicate tradeoffs and risks clearly, and mentor engineers through reviews and collaborative problem-solving.