About the Role
TheDirector of Data Platform & Operations serves as both the technical backbone and the people leader of our data organization: the architect who designs and builds our data infrastructure, the engineer who ships and maintains the pipelines that power it, and the primary technical point of contact bridging the business and the platform. This person will lead our Data Engineering, Data Governance, and BI/Analytics teams, own our BI strategy end to end, and lead the data foundation for our Glean AI implementation, ensuring the data feeding our AI search and knowledge tools is well-structured, governed, and trustworthy.
This is a hands-on leadership role: equal parts architect, engineer, people manager, and strategic partner to the business.
Why This Role Matters
Data is the foundation everything else gets built on: reporting, AI, and business decisions all depend on it being accurate, accessible, and well-architected. This role owns that foundation and is the go-to technical voice ensuring the rest of the business can trust and use it.
Responsibilities
Lead and grow the Data Engineering, Data Governance, and BI/Analytics teams
Set priorities, workflows, and quality standards across the three functions, ensuring they operate as one cohesive data organization
Mentor and develop team members, balancing hands-on technical guidance with career growth
Own hiring, performance management, and resourcing decisions for the team
Design and own the overall data platform: warehouse/lakehouse structure, schema design, and data modeling standards
Build, orchestrate, and maintain reliable data pipelines that move data from source systems into governed, analytics-ready models
Establish and enforce standards for data quality, dimensional modeling, and pipeline reliability
Manage cloud data infrastructure and associated cost optimization
Own the BI strategy - define how the business accesses trusted data, from executive dashboards to self-serve reporting
Build and evolve centralized reporting with appropriate access controls (RBAC)
Partner with department leaders to turn raw data into decision-ready insights and KPIs
Manage and own Data Platform roadmap and prioritization
Serve as the primary technical point of contact between the data platform and business stakeholders
Translate business requirements into scoped, deliverable technical initiatives
Act as a trusted advisor on what's possible with our data, and set realistic expectations on delivery
Own the data layer supporting our Glean implementation, ensuring source systems are properly connected, indexed, and governed for AI search
Partner with IT/AI stakeholders to define data access, quality, and security standards for AI-powered tools
Partner with the Agent Builder team to ensure AI agents are powered by trusted, governed data
Help shape the broader data strategy as AI becomes more embedded in daily workflows
Team Leadership
Data Architecture & Engineering
BI Strategy & Reporting
Technical Partnership to the Business
AI / Glean Data Ownership
Skills and Requirements
Experience architecting and delivering enterprise-scale data platforms and pipelines, including pipeline orchestration and scheduling (e.g., Azure, AWS, Databricks, Apache Spark)
Strong SQL/DDL skills and working proficiency in Python (or similar) for data engineering tasks
Experience with dimensional modeling and schema design, and hands-on ownership of a data warehouse or lakehouse (medallion architecture experience a plus)
Track record of building BI reporting and dashboards (Tableau, Power BI, or similar) with governed, centralized access
Experience integrating and normalizing data from core business systems (e.g., Salesforce, NetSuite, or similar enterprise platforms)
Comfort operating as both an individual contributor and a leader - this role builds pipelines and leads people
Experience managing a team, ideally spanning data engineering, data governance, and/or BI/analytics functions
Excellent communication skills; ability to be the "face" of the data platform to non-technical stakeholders
Experience with (or strong interest in) enterprise AI/knowledge tools like Glean is a plus
Background in high growth companies, preferably companies with heavy acquisition growth motions

