Data Solutions Lead

Equifax is seeking a highly skilled Data Solutions Lead to guide our Global Business Services (GBS) data engineering team. In this strategic role, you will act as the technical anchor for a squad of Data Engineers, ensuring that every solution we build is robust, secure, and compliant with corporate standards.

You will not work in isolation; instead, you will partner with Enterprise Architects to validate high-level designs and with Site Reliability Engineers (SREs) who manage the infrastructure provisioning. Your core mission is to bridge business needs with technical implementation: understanding requirements, proposing the initial technical design, validating its viability, and leading the team through execution. You will be the "guardian" of the platform, ensuring that new projects or updates maintain the integrity and stability of our Google Cloud environment and internal applications (Tracker & Meraki).

• Technical Implementation Leadership: Translate business requirements into concrete technical designs and solution intents. You will lead the engineering squad through the development and deployment phases, ensuring adherence to quality and security standards.

• Solution Design & Viability: Create initial technical designs for new data requests and collaborate with Enterprise Architects to validate their architectural viability and alignment with corporate strategy. Once approved, you will coordinate with SREs to provision, enable, and maintain the necessary infrastructure components throughout the project lifecycle.

• Platform & Pipeline Governance: Oversee the end-to-end lifecycle of data solutions. You are responsible for understanding how new components or updates affect the broader ecosystem, ensuring no negative impact on existing pipelines or platform stability.

• Engineering Best Practices & Mentorship: Guide the team in delivering high-quality code. You will provide technical direction, conduct code reviews, and ensure the team adheres to engineering handbooks.

• Operational Health: Drive continuous improvement by monitoring the health of the platform (using Datadog/Cloud Monitoring) and leading the resolution of complex data issues.

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

• 5+ years of total technical experience in Software Engineering or Data fields, with at least 3+ years of hands-on experience in Data Engineering on public cloud platforms (GCP preferred), building production-grade pipelines.

• 3+ years of technical proficiency in Python and SQL, covering data modeling, ETL/ELT design patterns, and automation processes, with the ability to assess how individual data requests impact overall platform architecture, stability, and compliance.

• 1+ year of experience in a Technical Leadership role, guiding developers, performing code reviews, and ensuring delivery quality.

• English proficiency of B2 or higher.

• Google Professional Data Engineer or Cloud Architect Certification.

• Cloud Specifics: Deep familiarity with GCP services like BigQuery, Cloud Composer (Airflow), and Cloud Functions (though AWS/Azure experience is welcome).

• Development Standards: Solid understanding of SDLC, CI/CD pipelines, and Software Security principles to ensure safe and efficient deployments.

• Backend & API Knowledge: Functional knowledge of Python-based backend frameworks (e.g., Django, Flask) and API design principles. Note: You will guide engineers on backend logic and integration strategies for our internal tools, though you are not expected to be the primary web developer.

• Data Quality Frameworks: Experience implementing automated testing or data quality checks (e.g., Great Expectations) within pipelines.

• ML/AI Exposure: Conceptual understanding of Machine Learning pipelines to support future AI initiatives within the platform.

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