Lead Data Engineer (AWS) — Data Pipelines & ML Enablement

State Farm; Richardson (TX); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work environment

Mentoring and leadership opportunities

Career development opportunities

Job summary

State Farm in Richardson, TX is seeking a Lead Data Engineer to join the SAIL team. You will design and deliver data capabilities for agency and digital experiences, collaborating with software engineers, product teams, and business partners to move, transform, and govern data in production-grade pipelines.

The role expects comfort with ambiguity, mentoring, and leading data engineering initiatives, with opportunity to guide ML/AI data workflows and contribute to architecture decisions in a

Qualifications

• 3+ years of Python development for data tasks and pipelines.
• Strong SQL skills and relational databases experience.
• Experience designing and maintaining ETL/ELT pipelines.
• Experience with CSV, JSON, and text data formats.
• Proficient with AWS services like S3, Glue, Lambda.
• Git and modern version-control practices.
• CI/CD practices and deploying to prod environments.
• Comfort with Linux and CLI environments.
• Knowledge of testing, observability, and maintainable design.
• Ability to troubleshoot data quality and performance issues.

Responsibilities

• Write code to move and transform data across systems.
• Collaborate with software engineers and product teams to access and analyze data.
• Design and maintain production-grade data platforms for structured and unstructured data.

Skills

Python development

SQL

ETL Pipelines

Data formats

AWS

Git

CI/CD

Linux

Software principles

Data quality

Tools

AWS S3

AWS Glue

AWS Lambda

Airflow

Job description

State Farm in Richardson, TX is seeking a Lead Data Engineer to join the SAIL team. You will design and deliver data capabilities for agency and digital experiences, collaborating with software engineers, product teams, and business partners to move, transform, and govern data in production-grade pipelines.

The role expects comfort with ambiguity, mentoring, and leading data engineering initiatives, with opportunity to guide ML/AI data workflows and contribute to architecture decisions in a