Director, Data Platforms and Operations

Job description

About the Role The Director 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 Team Leadership - 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 Data Architecture & Engineering - 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 BI Strategy & Reporting - 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 Technical Partnership to the Business - 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 AI / Glean Data Ownership - 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 ### 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