Mid-Level/Lead DA Engineer (GRAPH DATABASE ENGINEER): HYBRID

State Farm•Dunwoody, GA

1d•Hybrid

About The Position

State Farm is seeking an experienced DA Engineer to join its Claims Knowledge Graph team, which builds graph-based data solutions supporting claims investigations, including potential fraud, identity theft, and injury-related insights. The engineer independently designs, builds, and optimizes knowledge graphs that connect claims data and reveal relationships across entities. The role includes technical ownership of graph architecture and production deployment, development of reliable data pipelines, and use of graph analytics to support investigations and decision-making. The engineer collaborates with business partners, data analysts, data engineers, infrastructure engineers, and software engineers to turn business needs into scalable, production-ready graph solutions. The position is hybrid, with time spent both at an assigned facility and working from home. For Enterprise Technology, the arrangement requires approximately 40% in-office time each month beginning in late 2027. Hub locations are Richardson, Texas; Dunwoody, Georgia; Tempe, Arizona; and Bloomington, Illinois. Applicants must already be eligible to work lawfully in the U.S.; State Farm will not sponsor U.S. work authorization for this opportunity.

Requirements

At least five years of professional data engineering experience.
Hands-on experience developing and supporting graph database solutions using Neo4j, Amazon Neptune, or a comparable platform.
Ability to work independently and lead graph architecture and production deployment.
Experience designing labeled property graph models and writing and optimizing graph queries using a platform-appropriate language, such as Cypher or Gremlin.
Proficiency in SQL and at least one programming language, such as Python, Java, or Scala.
Experience building ETL or ELT pipelines, including integrating relational data into graph databases.
Understanding of graph algorithms and their application to analytical or investigative use cases.
Experience with data quality validation, automated testing, version control, and production troubleshooting.
Strong problem-solving, communication, and teamwork skills.

Nice To Haves

Experience with Apache Spark and Databricks for distributed data processing.
Experience with Neo4j Graph Data Science or comparable graph analytics libraries.
Experience with entity resolution, identity matching, or integrating data across multiple sources.
Familiarity with embeddings, including graph embeddings, vector similarity search, and machine learning applications involving graph data.
Experience using large language models to support engineering automation or knowledge graph workflows, such as information extraction and entity identification.
Experience developing or integrating APIs and microservices, including REST or GraphQL.
Experience with Docker, Kubernetes, and cloud infrastructure.
Experience with infrastructure as code using Terraform or OpenTofu and with CI/CD practices.
Familiarity with insurance claims, fraud analytics, or investigative decision support.
Technical ownership and leadership.
Cross-functional collaboration.
Clear technical and business communication.
Analytical thinking and problem-solving.
Business and insurance domain understanding.
Commitment to data quality, security, and operational reliability.

Responsibilities

Lead graph architecture decisions and design and maintain labeled property graph models, including entities, relationships, properties, and constraints, aligned with claims investigation use cases.
Build and maintain scalable pipelines to ingest, transform, validate, and load data from relational databases and other structured and unstructured sources into graph databases.
Lead the implementation, configuration, and production deployment of graph database solutions, such as Neo4j or Amazon Neptune, in collaboration with infrastructure teams.
Optimize graph queries, indexes, data models, and ingestion processes for performance, scalability, and resource utilization.
Apply graph algorithms such as community detection, centrality, and pathfinding to identify relationships, patterns, and investigative insights.
Implement automated testing, monitoring, data quality controls, and operational documentation to support reliable graph solutions.
Apply organizational standards for data access, privacy, security, and governance.
Translate business requirements into technical designs and communicate findings, tradeoffs, and recommendations to technical and business audiences.

Benefits

Annual raise and bonus; potential yearly incentive pay up to 15% of base salary.
Health and wellbeing programs, with State Farm paying most of the healthcare premium and multiple healthcare plan options.
Vision, dental, telemedicine, and access to 24/7 mental health professionals.
Educational benefits, including training programs and tuition assistance.
Employee resource groups and mentoring.
Fertility, IVF, and adoption assistance.
College coaching, national discount programs, financial workshops, and financial coaching.
Time off policies, with the opportunity to initially earn up to 20 days annually, plus parental leave, paid holidays, a celebration day, life leave, bereavement leave, and community service/education support days.
Matching Gift Program, Good Neighbor Grant Program, and Employee Assistance Fund.
401(k) plan with company contributions of up to 7% of salary.
State Farm Federal Credit Union savings and financing options.