Senior Data Engineer

Synopsis of the role

What You’ll Do

• Pipeline Engineering: Build and manage reliable data pipelines to aggregate, ingest, and process data from diverse source systems.
• Data Integration & Quality: Integrate, cleanse, and structure large datasets for analytical consumption and client solutions, implementing automated checks to troubleshoot data anomalies.
• Model Support: Apply an understanding of data characteristics to develop tracking processes that support data quality and entity resolution models.
• Cloud & Infrastructure: Leverage and implement Google Cloud Platform (GCP) technologies, keeping up with cloud advancements to propose optimization improvements.
• Data Governance: Implement data management, security, and maintenance best practices directly into pipeline workflows.
• Global Teamwork: Collaborate actively with regional and global Equifax teams to share insights, standardize workflows, and adopt best practices.
  

What Experience You Need

• Education: BS in a STEM major or equivalent discipline (Mathematics, Statistics, or Computer Science preferred).
• Experience: 3 to 5 years of hands-on experience in a data engineering or highly quantitative technical role.
• Core Tech Stack: Strong proficiency in Python and SQL, with practical experience writing utility scripts.
• Cloud Infrastructure: Competent understanding of cloud computing concepts, with practical experience working in Google Cloud Platform (GCP) or a similar cloud environment.
• Data Modeling: Experience transforming unstructured/structured data into optimized data models, troubleshooting pipeline bottlenecks, and ensuring data readiness.
• DevOps Basics: Solid experience with version control (Git) and exposure to CI/CD integration workflows.
  

What Could Set You Apart

• Big Data & Cloud Tooling: Hands-on experience with Google BigQuery, BigTable, Dataflow, or big data processing frameworks like PySpark/Scala.
• Data Formats: Familiarity with managing modern schemas and file formats such as JSON, AVRO, and PARQUET.
• Domain & Concept Knowledge: Exposure to credit/financial data products or prior project/academic experience with Entity Resolution and identity matching concepts.
• Certification: Any active cloud certifications (e.g., GCP Associate Cloud Engineer).