Data Engineer (Enterprise Data & AI, Intelligence Platform)

Riot Games; Los Angeles (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Healthcare plans

Family care

Paid time off

Retirement match

Play Fund

Donation matching

Job summary

Riot Games in Los Angeles seeks a Staff Data and AI Engineer to build governed data foundations powering analytics and AI. You’ll design data pipelines in Databricks, curate data models, and ship AI-enabled products with robust security and observability.

As a hands-on data and software engineer, you’ll own from architecture to production ops, partnering with enterprise stakeholders, and shaping semantic models in Unity Catalog for scalable enterprise solutions.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8+ years of experience in data engineering or related roles.
• Hands-on Databricks experience including Unity Catalog and medallion architecture.
• Proficiency in Python and core software engineering practices.
• Experience shipping production AI solutions (retrieval-augmented or agentic).
• Experience with GCP or AWS data services and dbt.

Responsibilities

• Build and operate production data pipelines in Databricks across Bronze, Silver, and Gold layers with lineage and logging.
• Define and evolve domain models in Unity Catalog with SMEs.
• Own data quality, tests, monitoring, and alerting for pipelines and products.
• Develop production agents and retrieval-augmented applications grounded in governed data.
• Apply engineering best practices: testing, reviews, CI/CD, and on-call support.
• Collaborate with enterprise systems through APIs, events, and middleware.

Skills

Python

Databricks

Unity Catalog

Medallion Architecture

LLM / AI platforms

Data engineering

Data governance

CI/CD

Observability

APIs / integration

Model serving

LangChain

Education

Bachelor’s degree in related field or equivalent

Tools

Vertex AI

OpenAI

Mosaic AI

dbt

Kubernetes

Job description

• As a Staff Data and AI Engineer on the Enterprise Data & AI team, you will build the governed data foundations that power enterprise analytics, automation, and applied AI
• Your primary focus will be data architecture and data engineering, where you will be responsible for designing and operating production data pipelines in Databricks, integrating & curating data through a medallion architecture, and defining semantic and domain models in Unity Catalog with subject-matter experts
• You will also build agents and retrieval-augmented applications directly on this governed data using Databricks capabilities such as Unity Catalog functions, Mosaic AI, and model serving
• You will own your systems from architecture through production operations, applying strong engineering, data quality, security, evaluation, and observability practices throughout
• The ideal candidate is a hands‑on data and software engineer who can turn ambiguous enterprise needs into reliable data products and focused AI‑enabled solutions
• The role will report to the Senior Manager, Enterprise Data and AI
• Data Pipelines and Semantic Layer (Primary):
• Build and operate pipelines that ingest source‑system data into Databricks using a medallion architecture across bronze, silver, and gold layers, with lineage, provenance, access controls, and logging
• Partner with subject‑matter experts to define and evolve domain, ontology, and semantic models in Unity Catalog, then curate reliable data products into those models
• Own data quality for the pipelines and products you build, implementing tests, monitoring, and alerting so issues surface before they reach downstream consumers
• Integrate enterprise systems through APIs, events, and middleware while applying appropriate authentication, retries, reconciliation, and auditability
• Agents on the Databricks Data Layer (Secondary):
• Build production agents and retrieval‑augmented applications grounded in governed Databricks data, using Unity Catalog functions as tools and Mosaic AI or model‑serving capabilities
• Add authorization, approvals, and auditability for consequential actions performed through agents or AI‑enabled orchestrations
• Create evaluation sets and observability for the agents you ship, including groundedness, latency, cost, and production feedback, and use the results to improve them
• Engineering Fundamentals:
• Apply solid engineering practices, including automated testing, code review, CI/CD, documentation, on‑call support, and concise design notes
• Own architecture decisions for your systems and communicate material tradeoffs clearly to technical and business partners

Benefits

• Healthcare: Medical, dental, and vision plans that cover you as well as your spouse/domestic partner and children.
• Family Care: Life insurance, parental leave, plus short and long‑term disability.
• Open Paid Time Off: In addition to holidays, a 2‑week end of year break, and a 1‑week mid‑year break, Rioters are trusted to take the time they need throughout the year.
• Retirement: Riot matches retirement contributions so you can continue to play games long after you retire.
• Play Fund: Riot’s annual play fund allows Rioters to broaden their knowledge of the games that matter to players and the community.
• Donation Matching: Riot matches donations of time and money to nonprofits to double down on support.

For this role, you’ll find success through craft expertise, a collaborative spirit, and decision‑making that prioritizes your fellow Rioters, who are the customers of your work. Being a dedicated fan of games is not necessary for this position

• Bachelor’s degree in a related field, or equivalent practical experience
• Experience integrating enterprise systems through APIs, events, or middleware, including authentication, retries, reconciliation, and auditability
• 8+ years of experience in data engineering, software or application engineering, or an adjacent enterprise technology role
• Proficiency in Python and strong software engineering fundamentals, including testing, code review, CI/CD, deployment, and production support
• Experience with an LLM or cloud AI platform such as Vertex AI, Anthropic, or OpenAI and an automation platform such as Workato, n8n, Camunda, or similar
• Hands‑on Databricks experience, including Unity Catalog, medallion architecture, and Mosaic AI or model serving
• Hands‑on experience building production data pipelines, including ingestion, semantic or domain modeling, data quality, and lineage
• Working knowledge of data governance, privacy, and security practices applied to production data pipelines and products
• Hands‑on experience shipping production AI solutions, such as retrieval‑augmented, conversational, or agentic applications, grounded in data pipelines you built
• Experience with dimensional modeling or master data management
• Experience with GCP or AWS data services, dbt, containers, or serverless computing
• Experience with enterprise or federated search, vector databases, or permission‑aware retrieval
• Experience with the Mosaic AI Agent Framework or Unity Catalog functions used as agent tools
• Experience with LLM or agent evaluation and observability, such as MLflow tracing
• Experience with agent frameworks such as LangGraph, Pydantic AI, LangChain, or CrewAI
• Experience integrating Workday, ServiceNow, Coupa, Concur, Oracle, OneStream, or Ironclad