Lead Data Engineer

State Farm•Bloomington, IL

2d•Remote

About The Position

State Farm (Bloomington, IL) seeks a Data Engineer to design and implement complex knowledge graph structures to enhance claims investigation and fraud detection through advanced graph analytics, collaborating with cross-functional teams to drive data-driven decision-making and innovation. Specific duties include: utilize industry-adopted languages and frameworks in coding, testing, security, DevOps, DataOps and data engineering practices using graph database technologies; develop and maintain reusable, scalable, and compliant data solutions across multiple platforms and compute environments ; be responsible for the identification, acquisition, cleansing, profiling, and ETL (extracting, transformation, and loading) of data used in analytic discovery and production solution deployment across multiple platforms; establish business domain knowledge for existing State Farm data sources and investigates, recommends, and initiates acquisition of data resources, both internal and external; identify and consult on emerging technologies and critical core systems, including techniques, tools, data sources, and platforms in the data engineering field; be familiar with handling datasets containing mixes of structured and unstructured data ; exhibit DataOps mindset where team is accountable for ensuring data aligns to enterprise needs and leveraging automation to deliver quality data solutions; collect and analyze information to identify customer's technical needs, suggest solutions and develop implementation and integration plans (e.g., technical proposals); be responsible for the analysis, design, deployment, support, and security of technology to ensure the organization is efficiently managing its technology and data-related assets in accordance with market best-practices and external regulations; apply a wide application of complex principles, theories, and concepts in computer science for data engineering solutions. Option to work remotely from anywhere in the U.S.

Requirements

Bachelor’s degree or foreign equivalent, in Computer Science, or a closely related field of study
5 years of experience in the job offered, or as a Specialist Programmer, or similar Machine Learning Engineer or Graph Data Engineer position
5 years of experience with working with graph database management systems (Neo4j or Amazon Neptune) and knowledge of Cypher Query Language
5 years of experience with distributed computing frameworks, including Apache Spark
5 years of experience utilizing developmental skills using programming languages, including Python or Java, and Scala
5 years of experience working with containerization and orchestration, including Docker, Kubernetes, leveraging Graph Algorithms Libraries, and Neo4j GDS

Responsibilities

utilize industry-adopted languages and frameworks in coding, testing, security, DevOps, DataOps and data engineering practices using graph database technologies
develop and maintain reusable, scalable, and compliant data solutions across multiple platforms and compute environments
be responsible for the identification, acquisition, cleansing, profiling, and ETL (extracting, transformation, and loading) of data used in analytic discovery and production solution deployment across multiple platforms
establish business domain knowledge for existing State Farm data sources and investigates, recommends, and initiates acquisition of data resources, both internal and external
identify and consult on emerging technologies and critical core systems, including techniques, tools, data sources, and platforms in the data engineering field
be familiar with handling datasets containing mixes of structured and unstructured data
exhibit DataOps mindset where team is accountable for ensuring data aligns to enterprise needs and leveraging automation to deliver quality data solutions
collect and analyze information to identify customer's technical needs, suggest solutions and develop implementation and integration plans (e.g., technical proposals)
be responsible for the analysis, design, deployment, support, and security of technology to ensure the organization is efficiently managing its technology and data-related assets in accordance with market best-practices and external regulations
apply a wide application of complex principles, theories, and concepts in computer science for data engineering solutions