State Farm is seeking a mid-level Data Engineer to help design and maintain scalable data pipelines and analytics assets, leveraging Python, AWS, and Spark. This hybrid role is based in Bloomington, IL, with arrangements that blend time in the office with remote work to support data initiatives across the organization.
Overview
State Farm emphasizes neighborly values, community investment, and responsible corporate citizenship. Join a leading data team to contribute to data-driven initiatives and make a meaningful impact.
Responsibilities
- Employs established languages and frameworks across coding, testing, security, DevOps, DataOps, and data engineering practices.
- Designs and maintains reusable, scalable, and compliant data solutions across multiple platforms and compute environments.
- Identifies, acquires, cleanses, profiles, and ETLs data used for analytic discovery and production deployments across various platforms.
- Develops business-domain knowledge of existing State Farm data sources and explores acquisition of internal and external data resources.
- Evaluates emerging technologies and core systems, including techniques, tools, data sources, and platforms in the data engineering field.
- Experienced with datasets that mix structured and unstructured data.
- Demonstrates a DataOps mindset, ensuring data aligns with enterprise needs and leveraging automation to deliver quality data solutions.
- Gathers and analyzes information to identify technical needs, proposes solutions, and develops implementation and integration plans (technical proposals).
- Oversees analysis, design, deployment, support, and security of technology to ensure efficient management of technology and data assets in line with best practices and external regulations.
- Applies a broad application of computer science principles to data engineering solutions.
Requirements
- 2-4 years of professional experience as a Data Engineer.
- Proficiency in Python, Spark SQL (or PySpark), R, Java, and Bash.
- Hands-on experience with AWS services including ETL tools (Glue, EMR Serverless), Lambda, Step Functions, EventBridge, S3, DynamoDB, Kinesis Firehose, Redshift, Iceberg, and SageMaker.
- Experience with distributed data processing frameworks such as Apache Spark and Databricks.
- Experience with infrastructure as code tools such as OpenTofu (formerly Terraform) for managing cloud resources and deployments.
- Familiarity with CI/CD pipelines including automated testing, security scans, and tools like Airflow.
Technologies
- Python
- Spark SQL / PySpark
- R
- Java
- Bash
- AWS Glue
- AWS EMR Serverless
- AWS Lambda
- AWS Step Functions
- AWS EventBridge
- AWS S3
- AWS DynamoDB
- AWS Kinesis Firehose
- AWS Redshift
- AWS Iceberg
- AWS SageMaker
- Apache Spark
- Databricks
- OpenTofu (formerly Terraform)
- Airflow
- SQL
- Athena
Benefits
- Get Paid!
- Stay Well!
- Develop and Grow!
- Plan Ahead!
- Take a Little “You” Time!
- Give Back!
- Finish Strong!
Hybrid
Qualified candidates must live within close proximity to a hub location and should plan to split time between home and the office as part of a hybrid work environment.
- Bloomington, IL
- Richardson, TX
- Tempe, AZ
- Dunwoody, GA
Sponsorship
Applicants must be eligible to work in the United States immediately; the employer will not sponsor U.S. work authorization (for example, H-1B visas) for this opportunity.
Application Deadline
The application window is expected to close on Friday, May 22, 2026 at 5:00 PM CT. Depending on volume and hiring needs, the period may extend or close sooner.
Competencies
- Adaptability
- Work Ethic
- Critical Thinking
- Strategic Business Focus
- Technical/Functional Expertise
