Director, Data Platforms and Operations

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 

• 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