Senior Data Engineer

General Information

Locations: Austin, Texas, United States of America

Role ID

214322

Worker Type

Regular Employee

Studio/Department

CT - IT

Work Model

Hybrid

Description & Requirements

Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.

The Senior Data Engineer is responsible for designing, building, and maintaining scalable data pipelines, data platforms, and architecture that support analytics, business intelligence, machine learning, AI, and agentic solutions. This role works closely with data scientists, analysts, AI/ML engineers, application teams, and business stakeholders to ensure data solutions are reliable, secure, scalable, and aligned with business needs and objectives.

Key Responsibilities

Analyze business and functional requirements; design, develop, and optimize data pipelines, workflows, and data services
Collaborate with data scientists, analysts, AI/ML engineers, product teams, and business stakeholders to gather requirements and deliver data solutions
Design and implement scalable ELT/ETL processes for large-scale structured, semi-structured, and unstructured data sets
Build and maintain data products that support analytics, reporting, machine learning, generative AI, retrieval-augmented generation, and intelligent agent workflows
Develop, operationalize, and optimize data pipelines that support AI and agentic systems, including data ingestion, transformation, feature preparation, metadata enrichment, and knowledge retrieval
Support AI/ML and GenAI initiatives by preparing high-quality, governed, and discoverable data for model training, evaluation, inference, and monitoring
Partner with AI teams to integrate enterprise data with vector databases, embeddings, knowledge graphs, semantic layers, APIs, and agent orchestration frameworks where appropriate
Ensure data quality, observability, lineage, integrity, and reliability across various data sources and downstream consumers
Monitor, troubleshoot, and optimize data pipeline performance, cost, scalability, and reliability
Perform code reviews and ensure solutions align with predefined architectural standards, engineering guidelines, security requirements, best practices, and quality standards
Optimize database, data warehouse, and lakehouse systems for performance, scalability, cost efficiency, and AI-readiness
Implement data security, privacy, governance, access control, and compliance measures across data and AI-enabled workflows
Understand and comply with the established software development life cycle methodology
Proactively identify opportunities for automation, process improvement, and platform modernization
Establish and enhance technical guidelines and best practices for the data engineering and integration development teams
Utilize subject matter expertise in enterprise applications and data solutions to evaluate complex, sensitive business problems and architect technical solutions
Mentor junior data engineers and provide technical guidance on data engineering, AI-enabling data patterns, scalable architecture, and engineering best practices
Stay current with emerging data, cloud, AI, GenAI, agentic AI, and data platform technologies

Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Engineering, Information Systems, or a related field
8+ years of experience leading design and development in BI, data engineering, or enterprise data environments scaling to hundreds of users and multiple terabytes of content
Proficiency in SQL and experience with relational databases
Knowledge of data warehousing and lakehouse solutions such as Snowflake, Redshift, BigQuery, Databricks, or similar platforms
Experience with big data technologies such as Hadoop, Spark, or distributed data processing frameworks
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud
Strong programming skills in languages such as Python, Java, JavaScript, or Scala
Strong understanding of RDBMS concepts, data modeling techniques including 3NF and dimensional modeling, database programming, and performance tuning
Experience designing reliable, scalable, and maintainable data pipelines for analytics, machine learning, or AI use cases
Familiarity with AI/ML data lifecycle concepts, including feature engineering, model-ready data preparation, data quality, evaluation data sets, and production data monitoring
Understanding of generative AI concepts such as embeddings, vector search, retrieval-augmented generation, prompt workflows, and enterprise knowledge retrieval
Familiarity with agentic AI patterns, including tool use, orchestration, workflow automation, memory, context management, and integration with enterprise systems
Experience applying data governance, security, privacy, and compliance controls to data products and AI-enabled systems
Excellent problem-solving, analytical, communication, and collaboration skills
Experience working in Agile methodology

Preferred Qualifications

Experience with real-time data processing and streaming technologies such as Kafka, Flink, Spark Streaming, or Kinesis
Experience with vector databases or search platforms such as Pinecone, Weaviate, OpenSearch, Elasticsearch, pgvector, Snowflake Cortex Search, or similar technologies
Experience supporting retrieval-augmented generation, enterprise search, semantic data layers, knowledge graphs, or AI-powered data products
Familiarity with AI agent frameworks or orchestration tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar technologies
Experience integrating data platforms with APIs, microservices, workflow orchestration tools, or internal developer platforms
Experience with MLOps, LLMOps, model monitoring, prompt/version management, or AI evaluation frameworks
Experience with data observability, lineage, cataloging, and governance tools
Experience in the gaming industry, digital entertainment, customer experience, or large-scale consumer data environments

About Electronic Arts

We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.

We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.

Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.

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