Director, Data Platforms and Operations

Responsibilities

Team Leadership

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• Lead and grow the Data Engineering, Data Governance, and BI/Analytics teams
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• Set priorities, workflows, and quality standards across the three functions, ensuring they operate as one cohesive data organization
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• Mentor and develop team members, balancing hands-on technical guidance with career growth
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• Own hiring, performance management, and resourcing decisions for the team

Data Architecture & Engineering

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• Design and own the overall data platform: warehouse/lakehouse structure, schema design, and data modeling standards
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• Build, orchestrate, and maintain reliable data pipelines that move data from source systems into governed, analytics-ready models
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• Establish and enforce standards for data quality, dimensional modeling, and pipeline reliability
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• Manage cloud data infrastructure and associated cost optimization

BI Strategy & Reporting

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• Own the BI strategy — define how the business accesses trusted data, from executive dashboards to self-serve reporting
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• Build and evolve centralized reporting with appropriate access controls (RBAC)
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• Partner with department leaders to turn raw data into decision-ready insights and KPIs

Technical Partnership to the Business

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• Manage and own Data Platform roadmap and prioritization
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• Serve as the primary technical point of contact between the data platform and business stakeholders
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• Translate business requirements into scoped, deliverable technical initiatives
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• Act as a trusted advisor on what's possible with our data, and set realistic expectations on delivery

AI / Glean Data Ownership

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• Own the data layer supporting our Glean implementation, ensuring source systems are properly connected, indexed, and governed for AI search
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• Partner with IT/AI stakeholders to define data access, quality, and security standards for AI-powered tools
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• Partner with the Agent Builder team to ensure AI agents are powered by trusted, governed data
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• Help shape the broader data strategy as AI becomes more embedded in daily workflows

Skills and Requirements

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• Experience architecting and delivering enterprise-scale data platforms and pipelines, including pipeline orchestration and scheduling (e.g., Azure, AWS, Databricks, Apache Spark)
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• Strong SQL/DDL skills and working proficiency in Python (or similar) for data engineering tasks
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• Experience with dimensional modeling and schema design, and hands-on ownership of a data warehouse or lakehouse (medallion architecture experience a plus)
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• Track record of building BI reporting and dashboards (Tableau, Power BI, or similar) with governed, centralized access
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• Experience integrating and normalizing data from core business systems (e.g., Salesforce, NetSuite, or similar enterprise platforms)
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• Comfort operating as both an individual contributor and a leader — this role builds pipelines and leads people
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• Experience managing a team, ideally spanning data engineering, data governance, and/or BI/analytics functions
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• Excellent communication skills; ability to be the "face" of the data platform to non-technical stakeholders
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• Experience with (or strong interest in) enterprise AI/knowledge tools like Glean is a plus
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• Background in high growth companies, preferably companies with heavy acquisition growth motions