Data Architect III

Location: Kirkland or Vancouver

The IPS (Infrastructure, Platform, and Services) organization provides the essential platforms and infrastructure solutions that power EA's live services and titles. Our mission is to ensure EA's games and services are available to all players, anytime and anywhere. We focus on high availability, scalability, and reliability of infrastructure and services, enabling rapid development and experimentation for our studios in the cloud and in the data center.

As a Data Architect III, you will be responsible for designing and implementing large-scale data solutions that support EA’s live services and analytics needs. You will architect and optimize data platforms, data lakes, and data warehouses, enabling advanced analytics, AI, and machine learning capabilities across hundreds of games and millions of players. You will report directly to a Senior Director IPS.

We offer a collaborative environment in our Kirkland WA facility, located near beautiful Caroline Point. You will work with a distributed team across multiple regions.

Responsibilities:

• Data Modeling & Catalog: Define logical and physical data models, implement a centralized metadata/catalog solution (e.g. DataHub, Glue Data Catalog) and enforce a semantic layer for self‑service analytics.
  
  

• Modern Pipelines: Design, build and optimize both batch ELT/ETL and real‑time streaming pipelines (using tools like Airflow, dbt, Spark Structured Streaming, Kafka, Flink or Materialize) for high throughput and low latency.
  
  

• Database & Warehouse Strategy: Lead selection, implementation and tuning of cloud data warehouses, lakehouses, and NoSQL (Snowflake, BigQuery, Databricks, Hadoop, Cassandra), including performance‑ and cost‑optimizations.
  
  

• ML/AI Enablement: Collaborate with Data Science/ML Engineering to provision feature stores, experiment tracking, and MLOps pipelines—ensuring data is discoverable, versioned, and lineage‑tracked.
  
  

• Governance & Security: Establish and enforce data governance standards, data‑quality frameworks (Great Expectations, Deequ), access controls (IAM, RBAC), encryption, and compliance (GDPR, HIPAA) across all environments.
  
  

• Technology Evaluation: Continuously research, prototype, and recommend emerging technologies (lakehouse architectures, serverless analytics, data mesh patterns) to improve agility, performance, and TCO.
  
  

• Cross‑Functional Partnership: Serve as the data‑infrastructure liaison to Product, Engineering, Analytics, and Operations—translating business requirements into robust data solutions and troubleshooting production issues.
  
  

• Leadership & Mentorship: Coach and guide data engineers on best practices (code reviews, CI/CD, testing), foster documentation culture, and evangelize data‑driven decision making across the organization.
  
  

The next great EA Data Architect also needs:

• 7+ years of professional experience in data architecture, data engineering, or related fields.

• Deep expertise in large-scale database systems (BigQuery, Snowflake, Spark, or similar).

• Strong background in batch ETL/ELT and streaming data architectures (e.g., Kafka, Spark, Flink).

• Familiarity with AI/ML data pipelines and supporting infrastructure.

• Proficiency in Python

• Has shipped an analytics platform that solved key business decisions with data driven insights.

• Experience with data governance, security, and compliance in large organizations.

• Excellent communication and collaboration skills, with a track record of working in distributed teams.