Success in this role requires strong technical ownership and effective teamwork. You will collaborate with business partners, data analysts, data engineers, infrastructure engineers, and software engineers to translate business needs into scalable, production-ready graph solutions.
Some Responsibilities May Include
Graph architecture and data modeling: Lead architectural decisions and design and maintain labeled property graph models, including entities, relationships, properties, and constraints, aligned with claims investigation use cases.
Data integration: Build and maintain scalable pipelines to ingest, transform, validate, and load data from relational databases and other structured and unstructured sources into graph databases.
Graph database engineering and deployment: Lead the implementation, configuration, and production deployment of graph database solutions, such as Neo4j or Amazon Neptune, in collaboration with infrastructure teams.
Performance optimization: Optimize graph queries, indexes, data models, and ingestion processes to improve performance, scalability, and resource utilization.
Graph analytics: Apply algorithms such as community detection, centrality, and pathfinding to identify relationships, patterns, and investigative insights.
Production reliability: Implement automated testing, monitoring, data quality controls, and operational documentation to support reliable graph solutions.
Security and governance: Apply organizational standards for data access, privacy, security, and governance.
Cross-functional collaboration: Translate business requirements into technical designs and communicate findings, tradeoffs, and recommendations to technical and business audiences.
Qualifications
We Are Seeking Candidates With
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.
Demonstrated 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 language appropriate to the platform, 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.
Additional Skills
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.
Core Competencies
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
Our Benefits
Because work-life balance is a priority at State Farm, compensation is based on our standard 38:45-hour work week!
Potential starting salary range: $97,000 - $177,000
Starting salary will be based on skills, background, and experience
High end of the range limited to applicants with significant relevant experience
Potential yearly incentive pay up to 15% of base salary
At State Farm, we offer more than just a paycheck. Check out our suite of benefits designed to give you the flexibility you need to take care of you and your family!
Get Paid! On top of our competitive pay, you are eligible for an annual raise and bonus.
Stay Well! Focus on you and your family’s health with our robust health and wellbeing programs. State Farm pays most of your healthcare premium, and we offer multiple healthcare plan options, including a high deductible plan. All medical plans provide 100% coverage for in-network preventative care, AND you and your family have access to vision, dental, telemedicine, 24/7 mental health professionals, and much more!
Develop and Grow! Take advantage of educational benefits like industry leading training programs, top-notch tuition assistance programs, employee resource groups, and mentoring.
Plan Ahead! Plan for those big moments in life with benefits like fertility/IVF/adoption assistance, college coaching, national discount programs, interactive monthly financial workshops, free financial coaching, and more. You can also start a savings account or consider financing through our State Farm Federal Credit Union!
Take a Little “You” Time! You will have access to our generous time off policies designed so you can plan around holidays, family events, volunteering, or just to take a relaxing day off. With the opportunity to initially earn up to 20 days annually plus parental leave, paid holidays, celebration day, life leave (40 hours/year), bereavement leave, and community service/education support days, there will be plenty of time for you!
Give Back! We offer several ways to give back through our Matching Gift Program, Good Neighbor Grant Program, and the Employee Assistance Fund.
Finish Strong! Plan for retirement using free financial advisors and a 401(k) plan with company contributions of up to 7% of your salary.
Visit our State Farm Careers page for more information on our benefits, locations, and the hiring process of joining the State Farm team!
We are seeking an experienced DA Engineer (GRAPH DATABASE ENGINEER) to join our Claims Knowledge Graph team. This team builds graph-based data solutions that support claims investigations, including the identification of potential fraud, identity theft, and injury-related insights.
As a Graph Database Data Engineer, you will independently design, build, and optimize knowledge graphs that connect claims data and reveal relationships across entities. This is an exciting opportunity to lead graph architecture and production deployment, develop reliable data pipelines, and apply graph analytics to support investigation and decision-making.
Success in this role requires strong technical ownership and effective teamwork. You will collaborate with business partners, data analysts, data engineers, infrastructure engineers, and software engineers to translate business needs into scalable, production-ready graph solutions.
Some Responsibilities May Include
Graph architecture and data modeling: Lead architectural decisions and design and maintain labeled property graph models, including entities, relationships, properties, and constraints, aligned with claims investigation use cases.
Data integration: Build and maintain scalable pipelines to ingest, transform, validate, and load data from relational databases and other structured and unstructured sources into graph databases.
Graph database engineering and deployment: Lead the implementation, configuration, and production deployment of graph database solutions, such as Neo4j or Amazon Neptune, in collaboration with infrastructure teams.
Performance optimization: Optimize graph queries, indexes, data models, and ingestion processes to improve performance, scalability, and resource utilization.
Graph analytics: Apply algorithms such as community detection, centrality, and pathfinding to identify relationships, patterns, and investigative insights.
Production reliability: Implement automated testing, monitoring, data quality controls, and operational documentation to support reliable graph solutions.
Security and governance: Apply organizational standards for data access, privacy, security, and governance.
Cross-functional collaboration: Translate business requirements into technical designs and communicate findings, tradeoffs, and recommendations to technical and business audiences.
We Are Seeking Candidates With
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.
Demonstrated 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 language appropriate to the platform, 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.
Additional Skills
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.
Core Competencies
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
