Senior Director, Data Platform & Engineering

We are looking for a Senior Director, Data Platform & Engineering to lead the Enterprise Data Platform and Enterprise Data Engineering functions within our Engineering & Innovation organization. This is a high-impact, high-visibility leadership role responsible for the infrastructure, pipelines, and tooling that power ZoomInfo's internal data ecosystem , serving stakeholders across Marketing, Finance, Product, Sales, HR, and Customer Success.

You will lead a team of approximately 30 engineers and contractors across two pillars:

• Enterprise Data Platform , owning Snowflake, cloud infrastructure (AWS and GCP), data lake architecture, ingestion frameworks, observability tooling, and security posture.
• Enterprise Data Engineering , owning pipeline development (Airflow, Fivetran), data modeling (dbt, semantic models), shift-left enablement, and AI-driven tooling for data practitioners.

This role sits at the intersection of infrastructure, engineering, and analytics enablement. You will set the strategic direction, drive platform modernization, and build the organizational systems that allow domain teams across ZoomInfo to own, trust, and act on their data.

You will do this through two experienced Directors who bring deep technical expertise , your job is to provide the vision, remove obstacles, and ensure the work connects to business outcomes.

Strategic Leadership & Team Development:

• Lead and develop two Director-level managers and their respective teams spanning data platform engineering, data pipeline development, and practitioner enablement.
• Set the multi-quarter roadmap for the Enterprise Data Platform and Engineering organizations, balancing infrastructure modernization, operational stability, security, and enablement priorities.
• Build a high-performance engineering culture grounded in ownership, accountability, and operational excellence.
• Drive headcount planning, organizational design, and career development frameworks that attract and retain top talent across a distributed team.

Platform Strategy & Infrastructure Modernization:

• Own the strategic direction for ZoomInfo's core data infrastructure, including Snowflake, Airflow, Fivetran, AWS, and GCP , partnering with the Director of Data Platform on architecture and execution.
• Guide the design and buildout of an Iceberg-based GCS Data Lake as the foundation for scalable, cost-efficient storage, including governance, observability, and ingestion patterns.
• Oversee cloud infrastructure consolidation to GCP, including Airflow 3.x upgrades, service migrations, and deprecation of legacy environments.

Data Engineering & Pipeline Operations:

• Oversee the development, reliability, and monitoring of all enterprise data pipelines powering analytics, reporting, and operational workflows , partnering with the Director of Data Engineering on execution and quality.
• Guide the evolution of data modeling practices through dbt and semantic models, ensuring data products are trusted, documented, and well-tested.

Cross-Functional Partnership & Enablement:

• Serve as the primary data infrastructure and engineering point of contact for leaders across Marketing, Finance, Product, Sales, and HR , translating business needs into platform capabilities.
• Partner with cross-functional stakeholders to define metrics, analytics requirements, and data delivery expectations that inform business strategy.

Requirements:

• 10+ years of progressive experience in data engineering, data platform, analytics, or related technical leadership roles, with at least 4 years at the Director level or above.
• Experience leading and scaling data organizations of 15+ people, with a track record of building high-performing teams and developing talent.
• Strong working knowledge of modern data stack technologies including Snowflake, dbt, Airflow, and cloud platforms (AWS and/or GCP).

Preferred:

• Familiarity with infrastructure-as-code practices (Terraform), CI/CD pipelines, and monorepo strategies.
• Experience with data lake architectures (Iceberg, Parquet) and multi-cloud environments.
• Exposure to data ingestion frameworks at scale (Fivetran, Airbyte, custom connectors) and reverse ETL patterns.
• Familiarity with AI/ML-driven automation for data engineering workflows, including agents and micro apps.