Experienced Data Engineer - Python, AWS & Spark (Hybrid)

State Farm; Richardson, Northern (TX, KY); Hybrid; USD 86,000 - 135,000; Full time

Benefits offered by this job

Starting salary range

Annual incentive pay

Health insurance

Tuition assistance

Retirement plan

Generous time off

Matching gifts

Financial planning

Career development

Job summary

State Farm is hiring an Experienced Data Engineer in Richardson, TX, to build and scale data products and pipelines that drive better business decisions and customer outcomes. This role sits in Enterprise Technology with a collaborative team and cross-team partnerships.

You will develop automated, reliable analytical data assets, apply DataOps principles, and work across platforms to deliver high-impact data solutions that support growth and retention.

Qualifications

• Professional data engineer with hands-on experience.
• Proficiency with Python/Scala/Java and SQL for data pipelines.
• Experience with AWS ETL tools, data processing frameworks, and data modeling.

Responsibilities

• Uses industry-standard languages and data engineering practices (DevOps, DataOps).
• Develops scalable, reusable data solutions across multiple platforms.
• Manages ETL/ELT data ingestion and transformation for analytics and production.
• Gathers domain knowledge of State Farm data sources and identifies data resources.
• Identifies emerging technologies and core systems relevant to data engineering.
• Supports data quality, security, and governance across pipelines, with monitoring.

Skills

Python/Scala/Java

SQL/Data modelling

AWS data services

CI/CD pipelines

Debugging/troubleshooting

Tools

Glue/EMR Serverless

Lambda/Step Functions

S3/Kinesis/Redshift

OpenTofu/Terraform

Spark/Databricks

GitHub/GitLab

Iceberg

Job description

State Farm is hiring an Experienced Data Engineer in Richardson, TX, to build and scale data products and pipelines that drive better business decisions and customer outcomes. This role sits in Enterprise Technology with a collaborative team and cross-team partnerships.

You will develop automated, reliable analytical data assets, apply DataOps principles, and work across platforms to deliver high-impact data solutions that support growth and retention.