Manager, Data Platform

We are seeking an experienced Manager, Data Platform to lead the strategy, architecture, and execution of our modern data platform supporting analytics, machine learning, operational systems, and AI-enabled applications. You will be a senior member of the larger AI, Data and Innovation organization, responsible for designing and expanding enterprise-level data infrastructure that enables ZoomInfo's internal teams to interact with data comprehensively. Our core tech stack includes Databricks, Snowflake, AWS, Spark, dbt, Fivetran, Airflow, and BigQuery.

This role combines hands-on technical leadership with people management. You will manage, mentor, and develop a team of data platform engineers while remaining deeply engaged in architecture, technical direction, platform reliability, and cross-functional planning.

The ideal candidate is a proven team builder who can translate business and stakeholder needs into scalable technical solutions across data engineering, cloud infrastructure, orchestration, governance, and observability.

What you’ll do

Technical Strategy & Architecture

• Define and evolve the vision, roadmap, and technical strategy for the data platform.
• Own architectural decisions across ingestion, transformation, orchestration, storage, serving, governance, and observability.
• Establish engineering standards and patterns for pipelines, data contracts, infrastructure, and deployment.
• Evaluate technologies, vendors, and architectural approaches in partnership with stakeholders.
• Remain hands-on in critical technical initiatives, architecture reviews, prototyping, and complex troubleshooting.

People Leadership & Management

• Manage, mentor, and develop a team of data platform engineers.
• Set clear expectations around technical execution, ownership, collaboration, and operational excellence.
• Support career growth through regular feedback, coaching, and performance management.
• Participate in hiring, onboarding, interviewing, and team capacity planning.
• Partner with leadership to define team structure, priorities, and long-term capability needs.

Platform Delivery & Operations

• Oversee the development and maintenance of reliable, scalable data pipelines and workflows.
• Establish service-level objectives (SLOs), data quality standards, monitoring, alerting, and incident response practices.
• Drive platform migrations and modernization efforts with a focus on incremental delivery and risk reduction.
• Reduce operational toil through automation, self-service capabilities, and standardized infrastructure.

Security, Governance & Data Contracts

• Establish appropriate access controls, data protection mechanisms, and security practices for sensitive data.
• Define and promote data contracts and clear ownership boundaries between source systems, data platforms, and downstream consumers.
• Improve data discoverability, lineage, and trust across the organization.
• Ensure platform architecture supports secure access for analytics, machine learning, and AI workloads.

Cross-Functional Collaboration

• Partner with application engineering, analytics engineering, data science, product, security, and infrastructure teams.
• Translate stakeholder needs into clear technical requirements and prioritized initiatives.
• Communicate architectural decisions, tradeoffs, and progress to both technical and non-technical audiences.

What you’ll bring

Required Qualifications

• 8+ years of experience in data engineering, data platforms, or data architecture.
• 2+ years of experience managing, mentoring, or leading data engineering teams.
• Demonstrated experience designing and operating production-grade data platforms and cloud architectures.
• Strong experience with data orchestration, transformation frameworks, and pipeline development.
• Strong understanding of data security, access controls, governance, and data contracts.
• Proven ability to balance hands-on technical contribution with people leadership.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience with AWS services (Redshift, S3, IAM, EKS, Glue, ECR, DMS).
• Experience with Python, SQL, Airflow, dbt, and Infrastructure as Code (IaC).
• Experience supporting machine learning platforms, LLM/AI access, or production ML services.
• Experience building or managing data contracts, semantic layers, or data interfaces.

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