Senior Software Engineer, Data Engineering

Roblox•San Mateo, CA

22h•$243,290 - $295,250•Onsite

About The Position

Roblox is seeking a Senior Software Engineer to design, build, and operate high-leverage data tooling used across the company. The role owns substantial technical work from problem discovery through production rollout, converting complex operational signals into clear, dependable workflows. A key focus 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. These capabilities should include strong evaluation, observability, and human oversight. The Tooling team builds shared systems that make data reliable, discoverable, governable, efficient, and easy to use. Its work spans data quality, lineage, metadata, ownership, observability, lifecycle management, optimization, and self-service workflows for Data Engineering, Data Science, Experimentation, Machine Learning, and product teams. Office-based roles are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday, unless otherwise noted.

Requirements

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

Nice To Haves

Familiarity with agentic workflows.

Responsibilities

Design, implement, and operate shared services, frameworks, and developer experiences for data quality, lineage, metadata, ownership, observability, lifecycle management, and optimization.
Turn freshness, quality failures, lineage, usage, and compute or storage cost signals into actionable alerts, recommendations, dashboards, and workflows.
Build AI-assisted or agentic experiences for investigating 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.
Own production readiness, including 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.