Equifax is seeking a skilled and motivated Data Engineer to support our GBS (Global Business Services) data initiatives. This role focuses on building, maintaining, and extending robust data pipelines to ensure critical business data is managed efficiently.

You will work primarily within a Google Cloud Platform (GCP) environment, utilizing Python and Airflow to automate data workflows and ensure high data quality. You will be responsible for monitoring the health of webapps and GCP services—such as Cloud Functions, Composer, Compute Engine, Cloud SQL, Dataflow, and BigQuery—and ensuring compliance with our Engineering Handbook. Additionally, you will play a key role in evolving our platform by researching new technologies and guiding teams through the release process.

What you'll do

• Pipeline Development: Design, develop, and maintain scalable Python-based data pipelines and workflows using Apache Airflow, utilizing Git and adhering to development best practices to support data solutions.

• Data Repository Management: Manage and optimize the BigQuery Repository and data structure, ensuring data quality, consistency, and compliance.

• Infrastructure Monitoring: Monitor the health and performance of webapps and cloud infrastructure components (e.g., Cloud Functions, Composer, Compute Engine, Cloud SQL, Dataflow) using cloud monitoring tools, providing support to minimize downtime.

• Continuous Improvement & Innovation: Constantly research, learn, and create Proofs of Concept (PoCs) to implement improvements in our GCP platform and data pipelines, utilizing new developments and GCP services to enhance our offerings as a platform provider.

• AI/ML Readiness: Research and prepare the cloud environment for AI/ML projects and initiatives, ensuring the platform is ready to support advanced data analysis capabilities.

• Release Management: Guide cross-functional teams in the release process to successfully deploy data solutions into the Production (PRD) environment, ensuring operational excellence.

What experience do you need

• A Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related technical field.

• 3+ years of professional experience in Data Engineering with strong proficiency in Python for pipeline creation and advanced SQL skills for querying and data modeling.

• Proven experience working with Cloud platforms (GCP is preferred), with a strong focus on Cloud Composer, Cloud Functions, BigQuery, and Cloud SQL.

• Solid knowledge of API usage, consumption, and creation, with experience integrating these into data workflows.

• English proficiency of B2 or higher.

What could set you apart

• Google Professional Data Engineer Certification or equivalent Cloud certifications.

• Conceptual understanding or practical experience with Machine Learning principles and their application in data processes.

• Experience with cloud infrastructure monitoring tools (e.g., Google Cloud Monitoring, Datadog) and incident response workflows.

• Familiarity with CI/CD pipelines and DevOps practices for data engineering. 

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