Senior Director, Data Platform & Engineering

ZoomInfo Technologies LLC•Remote, CA

3h•$231,000 - $363,000•Remote

About The Position

ZoomInfo is seeking a Senior Director, Data Platform & Engineering to lead the Enterprise Data Platform and Enterprise Data Engineering functions. This role is responsible for the infrastructure, pipelines, and tooling that power ZoomInfo's internal data ecosystem, serving various stakeholders across the company. The position involves setting strategic direction, driving platform modernization, and building organizational systems to enable data ownership, trust, and action. The role requires leading a team of approximately 30 engineers and contractors across two key areas: Enterprise Data Platform (Snowflake, cloud infrastructure, data lake, ingestion, observability, security) and Enterprise Data Engineering (pipeline development, data modeling, shift-left enablement, AI-driven tooling). 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.

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). You do not need to be the deepest technical expert — but you need to understand architecture trade-offs, ask the right questions, and make informed strategic decisions.
Experience driving platform modernization initiatives — whether 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) — translating ambiguous business needs into structured data solutions.
Experience building self-service analytics capabilities and enablement programs that reduce dependency on central engineering teams.
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 in both written and verbal formats.
Experience operating in fast-paced, high-growth, or transformation environments where priorities shift and adaptability is essential.

Nice To Haves

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, HIPAA, or SOC2.
Experience with data cataloging and lineage tools (OpenMetadata, DataHub, or similar).
Experience with shift-left or data mesh operating models where domain teams own their data end-to-end.
Exposure to BI platform management and modernization (Looker, Tableau, or emerging AI-driven visualization approaches).

Responsibilities

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.
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.
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.
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 — ensuring remediation of priority assets and retirement of low-value ones.
Oversee the buildout of centralized observability for certified metrics, including compliance monitoring, alerting, and automated routing of quality failures to asset owners.
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.
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 that have data implications.
Manage vendor relationships and contracts, negotiating strategically to optimize cost, capability, and long-term flexibility.