Principal Software Engineer, Creator Analytics

Roblox•San Mateo, CA

1d•$345,040 - $399,420

About The Position

Roblox is hiring a Principal Software Engineer for the Optimize team, which builds analytics and LiveOps tools used by creators to understand and grow their experiences. Products include Creator Hub analytics dashboards and benchmarks, custom events and funnels, experiments, Remote Configs, Segmentation, and supporting observability features. The role sets technical direction for the data systems behind these products and is accountable for their performance, reliability, and correctness at Roblox scale. The technology spans Kafka ingestion, Flink stream processing, Spark/Hive batch processing orchestrated with Airflow, Druid and StarRocks serving, and C# services supporting Experiments and Configs. The principal engineer will define the architecture and roadmap over the coming years, lead technically challenging work hands-on, and raise the engineering bar across the team. The team’s current focus is performance and reliability ahead of a high-traffic season. The role owns the strategy for making creator data faster, less expensive, and more trustworthy. It also involves setting the architecture for experimentation and LiveOps, partnering across organizations, mentoring senior engineers, and working with engineering, product, and design leadership on planning and prioritization. For roles based at Roblox’s San Mateo, California headquarters, the annual base salary range is $345,040–$399,420. The position is onsite Tuesday, Wednesday, and Thursday, with optional office presence Monday and Friday. Full-time employees are eligible for equity compensation and benefits. Roblox provides equal employment opportunities and reasonable accommodations during recruiting. For U.S.-based roles, the company may be unable to employ candidates with work authorization related to certain U.S. visa categories or support future H-1B sponsorship at this time.

Requirements

10+ years of professional software engineering experience, including 5+ years designing, building, and operating large-scale production data systems.
A track record of setting technical direction at principal/staff-plus level, defining architecture across multiple teams or systems and delivering measurable results.
Deep production expertise with Apache Kafka and Apache Flink, or equivalent streaming technologies, including event time, watermarks, windowing, state, and exactly-once/at-least-once trade-offs.
Experience with Apache Spark/Hive or equivalent warehouse/lakehouse processing, and Apache Airflow or equivalent DAG orchestration, including DAG design, SLAs, dependencies, and backfills at scale.
Experience with Apache Druid and/or StarRocks or equivalent real-time OLAP systems, including ingestion specifications, rollups, segment/partition design, and query tuning.
Experience shaping a company-scale shared data platform, such as shared ETL frameworks, standardized tables, and multi-team clusters.
Expertise in at least one of C#/.NET, Java/Scala, or Go, plus Python for pipelines and tooling.
Experience designing and operating gRPC/REST services at scale.
Experience defining SLOs, monitoring, and alerting using Grafana/Prometheus-style systems, and leading major production incident response and postmortems.
Clear, persuasive written communication, including strategy documents, technical specifications, and postmortems, and a record of building alignment across teams and with senior leadership.

Responsibilities

Own the multi-year architecture and roadmap for Optimize’s streaming, batch, and serving systems.
Decide what to build, buy, consolidate, or retire, and make trade-offs among data freshness, correctness, and cost explicit.
Write technical strategy documents and lead design reviews that set direction across the team.
Define standards for handling late and out-of-order data, backfills, replays, and data-quality validation.
Define SLOs and loss/lag alerting, including late-drop rate, consumer lag, and input-versus-output gaps.
Lead responses to serious data incidents, drive blameless postmortems, and ensure fixes address whole classes of failures.
Participate in the team’s PagerDuty on-call rotation.
Own capacity planning and load testing for seasonal pipeline peaks.
Lead performance work involving Kafka partitioning, Flink parallelism, state and checkpointing, and Druid/StarRocks ingestion and query serving.
Drive cost-efficiency strategy for storage retention, table lifecycle, and cluster right-sizing, with measurable targets.
Set architecture for Experiments, Remote Configs, and Segmentation, including assignment, sticky enrollment, targeting, exposure logging, and results pipelines.
Partner with IXP and Data Science on statistical correctness and metric definitions.
Represent Optimize in technical decisions with Data Platform, Streaming, Engine, and ESP on shared infrastructure.
Build alignment and drive multi-team initiatives to completion, influencing without authority.
Mentor senior engineers and develop future technical leaders.
Set engineering practices for design quality, operational excellence, and AI-assisted development.
Partner with engineering, product, and design leadership on planning and prioritization.