At Roblox, a deep understanding and measurement of users and creators' experience is critical to Roblox's rapid growth. The Analytical Data Engineering team is enabling Roblox's success through the development and maintenance of the Core Data model with an eye for scalability to support the analytical community and tooling to increase the speed at which we build data. As one of the founding members of the ADE team, you will define the data ontology for all of Roblox, define best practices and standards for the analytical community, define technical strategy for Roblox's ETL strategy including batch vs. streaming architecture, and influence event instrumentation.

As an Analytical Data Engineer you are familiar with supporting Data Science and Machine Learning workflows, and should leverage that knowledge to inform your design decisions and implementations. Our team's product will be the interface between data engineering and all other teams who will leverage the data to improve the Roblox platform and the experience of our users and creators alike.

You Will:

• Partner with science, product, and engineering to collect data requirements to define the Core Data Ontology for all of Roblox
• Lead a growing team of Analytical Data Engineers to support Roblox's ever-evolving data needs
• Design an extensible and scalable data model to support the ever growing analytical community
• Design, build, and maintain efficient and reliable data pipelines in batch and streaming to fuel the core data sets
• Apply ETL Frameworks to scale and extend functionality of the frameworks.
• Analyze the use cases for the data to determine appropriate SLAs
• Analyze the incoming data and upstream pipelines to determine and minimize epistemological issues.
• Determine appropriate relaxations to deterministic compute and leverage probabilistic data structures (bloom filters, count min sketch)
• Partner with the Data Platform Team to provide approximation algorithms (approximate nearest neighbor, etc.) for high use statistics of interest.
• Determine caching strategies and eviction policies to support cost-effective analysis
• Drive adoption of the Core Data tables and publicize new incoming datasets to ensure consistency across the organization

You Have:

• 8+ years of professional experience working with scalable ETL pipelines on industry standard ETL orchestration tools (i.e. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M).
• 3+ years working in the Hadoop Data Ecosystem for data processing
• 2+ years leading data engineering development directly with business or data science stakeholders.
• Built, scaled, and maintained Multi-Terabyte data sets.
• Experience with at least one major cloud's suite of offerings (AWS, GCP, Azure).
• Developed with Data Quality at the core of your pipelines (e.g. Great Expectations, Data Fold, etc.)
• Developed or enhanced ETL orchestrations tools
• Familiarity with Data Discovery tooling (e.g. Amundsen, Atlas)
• Worked within standard GitOps workflow (branch and merge, PRs, CI / CD systems)
• Familiarity with infrastructure configuration (IaC [e.g. Terraform], cluster parameter tuning, service parameter tuning)