Staff Data Engineer

About the role

In the role of Staff Data Engineer for Concepts Lab, you will report to the VP of the Concepts Lab. We are considering applicants for the location of Los Angeles, CA (onsite).

Core Areas of Responsibility

• Own the reliability of AI systems in the lab, including designing eval frameworks, instrumenting observability for LLM-based pipelines, and building the validation and structured-output layers that make model outputs trustworthy.

• Architect and build the end-to-end data foundation for Concepts Lab on Databricks (Delta Lake, Unity Catalog, Spark, Databricks SQL), spanning ingestion from AWS and GCP sources through to curated, analytics-ready datasets.

• Lead data modeling and transformation work by defining the dimensional models, semantic layers, and metrics that the lab and our partners across Crunchyroll rely on for experimentation and decision-making.

• Perform hands-on analytics: write the SQL, build the dashboards, and run the exploratory analyses that turn lab concepts into evidence, partnering directly with PMs and product leaders on the questions that matter.

• Set the technical bar for the lab’s data work, including design reviews, code quality, observability, cost management, and security practices, and mentor engineers and analysts who collaborate with us.

• Partner across teams to move successful concepts from prototype into production, working at the inflection point between central Data and Platform teams and upstream and downstream Software Engineering teams to hand off systems that scale beyond the lab.

About You

• You have 12+ years of professional experience building production data systems, with a track record of operating as a senior individual contributor or technical lead.

• You have hands-on experience making AI systems production-grade by designing trace-based evaluations, instrumenting observability for LLM pipelines (with tools like LangSmith, Langfuse, or Datadog), and enforcing structured outputs in real production environments.

• You possess deep expertise in Databricks, including Spark (PySpark and/or Scala), Delta Lake, Unity Catalog, Databricks SQL.

• You are equally strong in SQL and dimensional data modeling, and have shipped warehouse layers and semantic models that analysts and stakeholders actually trust and use.

• You write production-grade Python and have built data pipelines with modern orchestration tools (Airflow, Dagster, dbt, or similar) on AWS and/or GCP.

• You have done substantive analytics work yourself beyond just enabling others and can take an ambiguous business question and drive it to a clear, data-supported answer.

• You have experience working in early-stage, ambiguous environments where you define the problem as much as you solve it, and you know when to prototype quickly versus when to build for the long term.

Nice to Have Experience

• Experience in media, streaming, or gaming

• Experience working in an innovation lab, incubation environment, or R&D organization

• Experience with Datadog, Mixpanel, and Mux