Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you.
Workforce Solutions Data & Analytics (EWS D&A) is a high-energy, fast-growing organization within Equifax charged with building and supporting best-in-industry data assets and analytical solutions. We deliver solutions and insights to enable success for our customers, drive growth for our business, and create value for our shareholders.
As a Senior Data Engineer, you will lead the evolution of our data platform, and build data products, AI capabilities, and self-service solutions for the users of our data platform.

WHAT EXPERIENCE DO YOU NEED

• At least 7 years of experience in data engineering, data architecture, or a related field
• Strong understanding of data engineering principles and best practices, including data modeling, data warehousing, and data integration
• At least 3 years 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
• Bachelor’s degree or higher in Computer Science, Information Systems, or a related field

• Design and implement data engineering frameworks to scale development and deployment of data pipelines across the D&A organization
• Build complex batch and streaming pipelines to ingest data from upstream Equifax cloud systems
• Enable new GCP services and build self-service capabilities to enhance functionality of our data platform
• Act as a mentor to junior engineers within the Data Platform team and also the broader D&A organization
• 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