Senior Director, Data Platform & Engineering

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.
• Serve as a trusted partner to the VP of Engineering & Innovation, contributing to broader engineering strategy and organizational decisions.
• Establish clear prioritization frameworks to manage competing demands from security, infrastructure modernization, platform stability, and practitioner tooling.

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.
• Drive SaaS vendor strategy and cost optimization — evaluating build-vs-buy decisions for ingestion (Fivetran/Airbyte), cost management, and other platform tooling.
• Oversee monorepo consolidation and CI/CD standardization to enable consistent governance and accelerate deployment velocity.
• Ensure the platform team maintains a strong security posture including service account modernization, key rotation, legacy role decommissioning, access reviews, and incident response readiness.

Data Engineering & Pipeline Operations

• Oversee the development, reliability, and monitoring of all enterprise data pipelines powering analytics, reporting, and operational workflows.
• Guide the evolution of data modeling practices through dbt and semantic models, ensuring data products are trusted, documented, and well-tested.
• Champion the shift-left initiative, enabling product and engineering domain teams to own their data assets end-to-end while maintaining quality and standards.
• Support the development of AI-assisted tooling (agents and micro apps) that automate data engineering workflows — from ingestion and modeling to deployment and monitoring.
• Drive platform-wide data standards alignment for metadata, ownership, testing, and documentation.
• Oversee the buildout of centralized observability for certified metrics, including compliance monitoring, alerting, and automated routing of quality failures to asset owners.

Cross-Functional Partnership & Enablement

• Serve as the primary data infrastructure and engineering point of contact for leaders across Marketing, Finance, Product, Sales, and HR.
• Partner with cross-functional stakeholders to define metrics, analytics requirements, and data delivery expectations that inform business strategy.
• Drive enablement programs — documentation, training, office hours, and onboarding — to accelerate adoption of self-service data tools and standards across the organization.
• Represent the data platform and engineering organization in strategic planning conversations, company projects, and technology decisions.
• Manage vendor relationships and contracts, negotiating strategically to optimize cost, capability, and long-term flexibility.

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).
• Experience driving platform modernization initiatives — cloud migrations, tool consolidation, vendor transitions, or infrastructure redesigns.
• Demonstrated ability to manage through managers — setting direction, aligning priorities, and holding leaders accountable for outcomes without micromanaging execution.
• Proven cross-functional partnership skills with business stakeholders (Marketing, Finance, Sales, Product, HR).
• Experience building self-service analytics capabilities and enablement programs.
• Strong vendor management experience including contract negotiations, build-vs-buy evaluations, and SaaS cost optimization.
• Excellent communication skills — able to present strategy, trade-offs, and progress to executive leadership.
• Experience operating in fast-paced, high-growth, or transformation environments.

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 LLM-assisted tooling, agents, or semantic modeling frameworks.
• Background in security and compliance within data environments — RBAC, key rotation, masking.