Mid-Level/Lead Data Engineer-AWS & DB2 (HYBRID)

State Farm•Bloomington, IL

1d•Hybrid

About The Position

The Property & Casualty Data team is hiring a Data Engineer or Lead Data Engineer to support the Property & Casualty Data tool for the z/OS platform and related data modernization initiatives. The role engineers, maintains, and supports reliable data pipelines that extract data from legacy systems, make it available through tools, and deliver enterprise data into AWS for analytics and downstream consumption. The position supports the modernization of Property & Casualty data capabilities by helping transition critical data from legacy platforms to scalable cloud-based solutions while preserving accuracy, availability, security, and operational reliability. It is part of Enterprise Technology and involves collaboration across teams on complex data challenges and modern solutions aligned with enterprise goals. The role uses AWS services and enterprise data lake capabilities to simplify legacy processing, improve performance, automate operations, reduce technical debt, and migrate appropriate workloads from mainframe-based solutions to cloud architectures. The position is hybrid, with approximately 40% in-office time each month beginning in late 2027. Hub locations are Bloomington, Illinois, and Richardson, Texas. Applicants must already be eligible to work lawfully in the United States; sponsorship for work authorization is not available.

Requirements

Professional experience as a Data Engineer.
Proficiency in programming languages such as Python, Scala, Java, or Bash.
Hands-on experience with AWS services, including ETL tools such as Glue and EMR Serverless, Lambda, Step Functions, EventBridge, S3, Kinesis Firehose, Redshift, and Iceberg.
Experience with AWS-related solutions and technologies including ROSA, Databricks, Python, Go, GraphQL, Glue, EventBridge, S3, SNS, SQS, Iceberg, and Athena.
Strong understanding of mainframe and relational database systems.
Data access skills using SQL and Athena.
Experience designing, building, and maintaining data pipelines for automated data processing.
Experience with infrastructure-as-code tools such as OpenTofu (formerly Terraform) for cloud resource management and deployments.
Familiarity with CI/CD pipelines, automated testing, and security scans.
Knowledge of auditing and monitoring tools such as Dynatrace, AWS QuickSight, and CloudWatch.
Strong data domain knowledge and skills in Python or other data engineering languages, SQL optimization, automation, source control, troubleshooting, monitoring, and production support.
Ability to use industry-adopted languages and frameworks in coding, testing, security, and data engineering practices.
Ability to collect and analyze information, identify customers' technical needs, suggest solutions, and develop implementation and integration plans.
Ability to apply complex computer science principles, theories, and concepts to data engineering solutions and identify industry-standard solutions to complex problems.
Commitment to continuous delivery practices and familiarity with CI/CD, test-driven development, and paired programming.
Understanding of secure and compliant data handling, including access controls, auditability, retention, and sensitive-data considerations.
Strong troubleshooting, problem-solving, written and verbal communication, and collaboration skills.
Demonstrated ownership, initiative, adaptability, and ability to work across teams in a fast-paced, ambiguous, and changing environment.
Leadership abilities in planning, requirements, development, testing, and application service.

Responsibilities

Engineer, maintain, and support reliable data pipelines that extract data from legacy systems and deliver enterprise data into AWS for analytics and downstream consumption.
Support the Property & Casualty Data tool for the z/OS platform and associated data modernization initiatives.
Identify, acquire, cleanse, profile, and ETL data used in analytic discovery and production solution deployment across multiple platforms.
Develop and support data movement from legacy environments into AWS, including daily delta processing and cloud-based data consolidation.
Analyze, design, deploy, support, and secure technology and data assets in accordance with best practices and external regulations.
Identify opportunities to simplify legacy processing, improve performance, automate operational activities, reduce technical debt, and transition appropriate mainframe workloads to cloud architectures.
Monitor daily processing, troubleshoot failures, perform root-cause analysis, implement recovery procedures, and develop long-term solutions that reduce manual intervention and improve operational reliability.
Plan and contribute to application requirements, development, unit, integration, regression, and performance testing, and service support.
Collaborate with technical and business partners, explain data concepts clearly, and contribute to solution designs focused on performance, risk mitigation, and supportability.

Benefits

Annual raise and bonus, with potential yearly incentive pay up to 15% of base salary.
Health and wellbeing programs, with State Farm paying most of the healthcare premium and multiple medical plan options.
Vision, dental, telemedicine, and access to 24/7 mental health professionals.
Educational benefits, industry training, tuition assistance, employee resource groups, and mentoring.
Fertility, IVF, and adoption assistance.
National discount programs, financial workshops, and free financial coaching.
Generous time-off policies, initially up to 20 days annually, as well as parental leave, paid holidays, celebration day, life leave, bereavement leave, and community service/education support days.
Matching Gift Program, Good Neighbor Grant Program, and Employee Assistance Fund.
401(k) plan with company contributions of up to 7% of salary.
Flexible work schedules to support work-life balance.