Data Analytics Engineer

$113,250 - $210,000/Yr

State Farm - Bloomington, IL

Full-time - Entry Level

Remote - Bloomington, IL

10,001+ employees

Insurance Carriers and Related Activities

About the position

As a Data Analytics Engineer at State Farm, you will play a crucial role in developing modeling solutions and maintaining data pipelines to support data-driven decision-making across various business units. This position involves collaboration with data scientists and business experts to enhance data services and automation, while also investigating new data resources and technologies to improve analytical capabilities.

Responsibilities

• Work closely with data scientists and business experts to develop modeling solutions for various internal business partners.
• Build and maintain data pipelines for the development, implementation, execution, validation, monitoring, and improvement of data science solutions.
• Enable data driven decision making by applying data analytic techniques, and exploratory research and analysis.
• Understand data infrastructure needed to support data services and automation.
• Establish business domain knowledge for State Farm data sources.
• Investigate, recommend, and initiate acquisition of new data resources from internal and external data sources.
• Identify critical and emerging technologies, techniques, tools, data sources, and platforms in the data engineering field.

Requirements

• Completed bachelor's degree in computer science, software engineering, data science, or related field.
• 2+ years of professional, post-internship work experience in a computer science- or technology-related field.
• Minimum of 2 years of experience with the Python 3+ programming language and relevant libraries (e.g., Pandas, Numpy).
• Practical experience with building SQL queries.
• Experience in gathering and creating analytic business requirements, researching data sources (internal and external), and developing and maintaining data assets.
• Experience with developing solutions on AWS or other distributed compute platforms.
• Ability to learn and adopt new technologies and languages.
• Experience with data analysis, particularly descriptive and exploratory analysis.

Nice-to-haves

• Experience with AWS technologies such as Lambda, Athena, Glue, S3, IAM, and Redshift.
• Working experience with PySpark for data manipulation and processing.
• Proficiency with building and maintaining data pipelines.
• Experience with CI/CD systems, preferably GitLab.
• Familiarity with the model development life cycle.
• Experience with infrastructure as code, preferably with Terraform.
• Understanding of Generative AI technologies such as vector databases and RAG.
• Strong communication skills and the ability to collaborate closely with different roles including data scientists, machine learning engineers & other business partners.

Benefits

• 401(k)
• Continuing education credits
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Tuition reimbursement