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Tier-1 brand, popular Data Engineer title, mid-level role and metro location drive high applicant density.
Core data engineering skills transferable, but LLM and game-infrastructure specifics increase domain sensitivity.
Multiple mandatory technical skills including cloud, lakehouse, Airflow and LLM experience increases screening rigidity.
Design and deliver foundational data services, pipelines, and analytics systems supporting EA's critical infrastructure across multiple games.
Build and deploy AI agentic workflows using LLMs to automate data engineering tasks like schema inference, pipeline scaffolding, anomaly triage, and incident summarization.
Create interactive dashboards and visualizations that provide actionable insights into infrastructure telemetry for engineering and leadership teams.
Experience with database technologies such as MySQL, MongoDB, or Cassandra.
Experience with data lakehouse architectures and OLAP data warehouses like BigQuery, DeltaLake, Snowflake, or Redshift.
Proficiency in programming languages such as Python, Java, and/or Go and experience with public cloud providers (AWS, GCP, Azure).
Bachelor's degree in Computer Science or equivalent; Work Experience Required: Not explicitly mentioned in the JD.
Familiarity and hands-on experience with LLMs and agentic AI frameworks (e.g., LangChain, LangGraph) for workflow automation.
Experience integrating AI agents into operational tooling for natural language querying and root-cause analysis.
Background in building scalable data infrastructure supporting large, complex gaming environments and real-time telemetry analysis.