MID-LEVEL DATA ENGINEER-Python, AWS, Spark (Hybrid)

State Farm•Dunwoody, GA

2d•Hybrid

About The Position

Our Property & Casualty Data Pipeline team is hiring an Experienced Data Engineer to help advance one of the company’s highest priorities. In this role, you will build and scale the data products and pipelines that power better business decision, profitable growth, and stronger customer retention. You will develop automated, reliable analytical data assets that help transform how we operate and how we serve our customers. This position sits within Enterprise Technology and offers the opportunity to work in a highly collaborative environment focused on delivering meaningful business impact. You will partner across teams, solve complex data challenges, and help shape modern data solutions aligned to enterprise goals. It is a strong fit for someone who wants to expand their technical skills, work on high-visibility initiatives, and contribute in a fast-moving, innovative setting.

Requirements

Minimum of 2-4 years of professional experience as a Data Engineer.
Proficiency in programming languages such as Python, Spark SQL (or PySpark), R, Java, Bash, etc.
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, 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.
Data access skills using SQL, and Athena.
Experience in designing, building, and maintaining data pipelines for automated data processing.
Knowledge of data modeling techniques such as star schema and snowflake schema, with an understanding of data architecture.

Nice To Haves

Experience or ability to rapidly gain P&C data domain knowledge, including rating, underwriting, and/or claims.
Experience with relational databases such as DB2, Postgres, Redshift, etc.
Experience with version control systems such as GitHub or GitLab.

Responsibilities

Utilizes industry-adopted languages and frameworks in coding, testing, security, DevOps, DataOps and data engineering practices
Develops and maintains reusable, scalable, and compliant data solutions across multiple platforms and compute environments
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
Establishes business domain knowledge for existing State Farm data sources and investigates, recommends, and initiates acquisition of data resources, both internal and external
Identifies and consults on emerging technologies and critical core systems, including techniques, tools, data sources, and platforms in the data engineering field
Familiar with handling datasets containing mixes of structured and unstructured data
Exhibits DataOps mindset where team is accountable for ensuring data aligns to enterprise needs and leveraging automation to deliver quality data solutions
Collects and analyzes information to identify customer's technical needs, suggest solutions and develop implementation and integration plans (e.g., technical proposals)
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
Applies a wide application of complex principles, theories, and concepts in computer science for data engineering solutions