Electronic Arts

Electronic Arts Inc. is a global leader in interactive entertainment. We develop games, content and online services across platforms. We have a broad portfolio of brands that span the most popular genres.

We exist to Inspire the World to Play. We create extraordinary new game experiences for our millions of players everywhere by bringing together experienced people that combine creativity, innovation, and passion. We celebrate diversity and inclusion and aim to create great experiences for our employees as often as our players. We're looking for people to come to the office or Zoom meeting excited to work and ready for some fun. The Senior Data Engineer will report to Sr Manager Engineering responsible for Data & Insights. 

Join us in driving the next revolution in games.

Responsibilities: 

 •  Design, build, and optimize scalable data acquisition, transformation, and integration pipelines to meet evolving business requirements.

 •  Develop, maintain, and automate ETL/ELT processes to extract, transform, and load data from diverse sources into analytical and operational systems with high accuracy and timeliness.

 •  Optimize data integration systems for scalability, performance, and reliability as data volume and complexity increase.

 •  Create and maintain logical and physical data models, ensuring efficient data storage, retrieval, and integration across platforms.

 •  Collaborate with cross-functional teams to define and implement data strategies, data flows, and conceptual models aligned with enterprise architecture standards.

 •  Ensure data quality, consistency, and governance by implementing validation, lineage, and monitoring frameworks.

 •  Analyze complex data sets to design business intelligence, analytics, and integration solutions.

 •  Translate business requirements into technical designs and scalable implementations using modern data engineering tools and practices.

 •  Develop and optimize complex SQL queries, stored procedures, and automation scripts using SQL, Python, and/or JavaScript.

 •  Leverage APIs and Python-based automation to streamline data workflows and improve processing efficiency.

 •  Apply prompt engineering and natural language processing (NLP) techniques to enable AI-driven data querying and insight generation.

 •  Integrate machine learning models into data pipelines where applicable to support predictive and prescriptive analytics use cases.

 •  Implement data observability and monitoring solutions to proactively identify and resolve issues.

 •  Follow best practices for programming, documentation, version control, and CI/CD in data integration projects.

 •  Develop and document data audit, archiving, and restoration procedures.

 •  Review and refine integration development efforts to ensure consistency, security, and adherence to best practices.

Qualifications: 

 •  Bachelor's or Master's degree in IT, Computer Science, or equivalent experience..

 •  7+ years of experience in data integration, data engineering, or related roles, with a proven track record of delivering scalable data solutions.

 •  5+ years of hands-on experience designing and implementing ETL/ELT pipelines and data integration frameworks.

 •  2+ years of experience in data modeling (conceptual, logical, and physical).

 •  Advanced proficiency in Snowflake, including its advanced features and utilities.

 •  Strong understanding of data structures, database systems, and data warehousing principles, along with exposure to data mining and analytics techniques.

 •  Proficiency in Python for data automation, API integration, and scripting; experience with JavaScript is an added advantage.

•  Familiarity with cloud-based data ecosystems (AWS, Azure, or GCP) and modern orchestration tools (Airflow, dbt, or similar).

•  Exposure to or interest in AI/ML integration within data pipelines, including feature engineering, model operationalization (MLOps), and intelligent automation.

•  Experience or interest in prompt engineering and NLP-based querying to enable AI-driven data insights.