Senior Data Engineer

You will be part of a high-energy, fast-growing organization within Equifax charged with building and supporting best-in-industry data assets and analytical solutions. This role will be working on our Ignite AI Advisor application. We deliver solutions and insights to enable success for our customers, drive growth for our business, and create value for our shareholders.

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.

Equifax has a hybrid work schedule that allows for 2 days of remote work (Monday and Friday), with 3 required onsite days (Tuesday, Wednesday, Thursday) every week.

This role will work the required onsite days at our Equifax office in Alpharetta, GA.

This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

This position is not open to third-party vendors or C2C.

• 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 Ignite landscape.
• 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.
• You will get to work on our high visibility Ignite AI advisor project.

• Bachelor’s degree or equivalent experience.
• 5+ years of experience in data engineering, data science, data architecture, or a related data field.
• A strong understanding of data engineering principles and best practices, including data modeling, data warehousing, and data integration.
• 5+ years experience working with software design with Java, Python, SQL, and JavaScript programming languages.
• 5+ years experience with software build management tools like Maven or Gradle.
• 5+ years experience with Cloud technology: GCP, AWS, or Azure.
• Proficiency with continuous integration and continuous delivery tooling and practices - Jenkins, Docker, Kubernetes.

• Building and maintaining complex data pipelines and solutions.
• Self-starter that identifies/responds to priority shifts with minimal supervision.
• 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., Lang Chain, Llama Index).
• Experience integrating AI services and models into data pipelines via APIs.
• Dev Ops/CICD experience (Jenkins and Git Hub) and IaC experience using Terraform for managing GCP infrastructure.
• GCP Associate Cloud Engineer or Professional Data Engineer certification.