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Principal Software Engineer (Data Engineering)

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Onsite

Principal Software Engineer (Data Engineering)

Roblox

Principal Software Engineer (Data Engineering)

Skills

Google Cloud PlatformSQL QueriesData EngineeringData ScienceData AnalysisMachine LearningAWSPySparkApache AirflowAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

$295,250 – $345,040 / year

Location:

San Mateo, CA, USA

Work mode:

Onsite

Published on:

21 October 2026

What they need


  • The Data Engineering team at Roblox plays a crucial role in enabling the company’s success by developing and maintaining highly leveraged Core Data Sets, frameworks, and tooling to support the growing demand for analytics

  • As a Principal Data Engineer, you will work to define the data ontology for all of Roblox, establish best practices and standards for data operations and lifecycle management, design and build analytics tooling and frameworks, and influence event instrumentation

  • Additionally, this role is highly cross-functional, requiring close collaboration with Data Science, Experimentation, and Machine Learning teams to understand customer requirements and analytics applications, as well as with Data Infrastructure and Storage teams to develop integrated solutions

  • Partner with Data Science, Data Platform, Product, and Engineering to collect requirements to define the data ontology for all of Roblox

  • Lead and mentor a growing team of Data Engineers to support Roblox’s ever-evolving data needs

  • Design, build, and maintain efficient and reliable batch and streaming data pipelines to model business entities as core data sets

  • Develop scalable frameworks and tooling to automate analytics workflows and streamline users interactions with data products

  • Establish and evangelize best practices for data operations and lifecycle management

  • Experience with at least one major cloud’s suite of offerings (AWS, GCP, Azure)

  • Built, scaled, and maintained Multi-Terabyte data sets and have an expansive toolbox for debugging and unblocking large scale analytics challenges (skew mitigation, sampling strategies, accumulation patterns, data sketches, etc.)

  • Worked within standard GitOps workflow (branch and merge, PRs, CI / CD systems)

  • Developed or enhanced ETL orchestrations tools or frameworks

  • 3+ years leading data engineering development directly with business or data science stakeholders

  • 8+ years of professional experience working building scalable ETL pipelines on industry standard ETL orchestration tools (Airflow, Dagster, Luigi, Google Cloud Composer, etc.) with deep expertise in SQL, PySpark, or scala

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