Job Description

Overview

We are not just offering a job but a meaningful career! Come join our passionate team!

As a Fortune 50 company, we hire the best employees to serve our customers, making us a leader in the insurance and financial services industry. State Farm embraces diversity and inclusion to ensure a workforce that is engaged, builds on the strengths and talents of all associates, and creates a Good Neighbor culture.

We offer competitive benefits and pay with the potential for an annual financial award based on both individual and enterprise performance. Our employees have an opportunity to participate in volunteer events within the community and engage in a learning culture. We offer programs to assist with tuition reimbursement, professional designations, employee development, wellness initiatives, and more!

Visit our Careers page for more information on our benefits, locations and the process of joining the State Farm team!

REMOTE:  Qualified candidates (outside of hub locations listed below) may be considered for 100% remote work arrangements based on where a candidate currently resides or is currently located.

HYBRID:  Qualified candidates (in or near hub locations listed below) should plan to spend time working from home and some time working in the office as part of our hybrid work environment.

Hybrid work arrangement for Enterprise Technology is defined as residing with a 180-mile radius of the Hubs and Corporate.  

SPONSORSHIP: Applicants are required to be eligible to lawfully work in the U.S. immediately; employer will not sponsor applicants for U.S. work authorization (e.g., H-1B visa) for this opportunity.  

Responsibilities

As a Graph Data Engineer, candidate will play a crucial role in leveraging knowledge graphs to drive data-driven decision-making for claims operations. Primary responsibilities will include designing, modelling, and implementing complex data structures as graphs, ensuring efficient data storage and retrieval, developing scalable solutions using graph databases, and applying graph algorithms for advanced analytics.  Candidate will closely collaborate with business partners, data analysts and software engineers to transform data into actionable insights through graph technology.

Claims Knowledge Graph team develops Knowledge Graphs for Claim investigation process to identify potential fraudulent claims, provide graph insights for decision support and provide connected contextual data for GenerativeAI use cases within claims.

Joining this team will provide an opportunity to work in cutting-edge highly technical capabilities withing State Farm and be an innovator in the Graph space.

Qualifications

We are looking for data engineers who have a variety of different skills which include some of the below.

Minimum of three (3) years work experience as a Graph Data Engineer in business environment
Knowledge Graph Technologies (e.g., RDF, OWL)
Graph Database Management Systems (e.g., Neo4j, TigerGraph, TypeDB, Amazon Neptune)
Data Modeling Tools (e.g., GraphQL - Galaxy Modeler)
Data Integration and ETL Tools (e.g., Apache Kafka, Apache NiFi)
Query Languages (e.g., SPARQL, GraphQL, Cypher)
Distributed Computing Frameworks (e.g., Apache Spark)
Graph Algorithms Libraries (Neo4j GDS libraries)
Programming Languages (e.g., Python, Scala, Java)
Containerization and Orchestration (e.g., Docker, Kubernetes)
Knowledge of event-streaming platforms such as Kafka

Additional Skills/Qualifications:

Knowledge Graph Development: Create and maintain knowledge graphs by modelling structured and unstructured data into graph representations, enabling efficient traversal and analysis
Data Modeling: Develop data models to define the structure and relationships within the graph, ensuring data accuracy and consistency
Graph Database Implementation/Deployment: Lead the implementation and deployment of graph databases (e.g., Neo4j, Dgraph, TigerGraph, TypeDB, Amazon Neptune) within our infrastructure, optimizing performance and scalability
Graph Algorithms: Apply graph algorithms (e.g., PageRank, community detection, shortest path) to extract valuable insights and patterns from the knowledge graph, driving data-driven decision-making
General Data Engineering Skills: Collaborate with cross-functional teams to ingest, transform, and load data from various sources into the knowledge graph, ensuring data quality and reliability
Query Optimization: Optimize graph queries to enhance query performance and reduce response times for complex analytical tasks