Data Engineer

Equifax • St. Louis, MO

5d • Hybrid

About The Position

As a Data Engineer, you will play a crucial role in the evolution of our data platform, support the activation of AI capabilities across the team, and build data products and self-service solutions for the users of our data platform. This role requires being in the office 3 days/week on Tues - Thurs. This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

Requirements

• At least 5 years of experience in data engineering, data architecture, or a related field.
• A strong understanding of data engineering principles and best practices, including data modeling, data warehousing, and data integration.
• At least 1 year of experience working in a GCP big data environment.
• Experience building complex data pipelines and solutions using two or more of the following: BigQuery, DataFlow, DataProc, Pub/Sub, Cloud Functions.
• Experience with Airflow or Cloud Composer.
• Experience with Vertex AI.
• Proficiency in Python development.
• Professional experience with SQL.
• Proven ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.
• A Bachelor's degree or higher in Computer Science, Information Systems, or a related field.

Nice To Haves

• Demonstrated experience with prompt engineering to interact with and guide AI models for optimal outputs.
• Hands-on experience with AI-assisted coding tools
• Familiarity with frameworks for building AI applications or agents (e.g., LangChain, LlamaIndex).
• Experience integrating AI services and models into data pipelines via APIs
• DevOps/CICD experience (Jenkins and GitHub) and IaC experience using Terraform for managing GCP infrastructure.
• GCP Associate Cloud Engineer or Professional Data Engineer certification.

Responsibilities

• Build complex batch and streaming pipelines to ingest data from upstream Equifax cloud systems.
• Design and implement data engineering frameworks to scale the development and deployment of data pipelines across the D&A organization.
• Leverage AI-powered coding assistants to accelerate development, optimize code, and generate documentation for data pipelines and infrastructure.
• Develop and refine prompts for Large Language Models (LLMs) to assist in data-related tasks such as data cleansing, transformation logic generation, and automated data documentation.
• Design, build, and maintain scalable data pipelines that support AI/ML applications.
• Explore and implement AI agents to automate repetitive data management tasks, monitor data quality, and orchestrate complex data workflows.
• Play an active role in setting engineering standards and best practices in EWS D&A.

Benefits

• comprehensive compensation and healthcare packages
• 401k matching
• paid time off
• organizational growth potential through our online learning platform with guided career tracks

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level