Manager, Data Platform Governance & Operations

Accountabilities:

• • Define and evolve the enterprise data governance strategy, covering RBAC, compliance frameworks, platform security, cost optimization, self-service access, and AI/ML governance maturity.
  • Own the governance architecture for Snowflake, AWS, and emerging data platforms, ensuring strong security, compliance, cost efficiency, and operational scalability.
  • Partner with platform and engineering teams to embed governance capabilities such as role-based access, network security, data masking, and Iceberg integration into enterprise data environments.
  • Establish governance foundations for AI and ML initiatives, including model governance, AI data lineage, responsible data-use policies, and management of Snowpark ML assets.
  • Operationalize governance standards through automated policies, controls, monitoring, reporting, and continuous compliance validation.
  • Lead SOX and related compliance activities, including access controls, audit evidence, segregation-of-duties monitoring, and automated compliance processes.
  • Oversee data catalog and metadata governance, ensuring accurate lineage, PII classification, masking policies, stewardship practices, and data-domain accountability.
  • Establish governance monitoring and reporting capabilities to identify anomalies, measure compliance posture, and provide leadership with actionable visibility.
  • Own Snowflake and AWS platform economics, including warehouse sizing, compute optimization, cost attribution, chargeback models, resource monitoring, and cost-reduction initiatives.
  • Measure and communicate platform ROI, governance effectiveness, audit-risk reduction, compliance improvements, and cost trends to senior leadership.
  • Build, mentor, and scale a high-performing governance engineering team, including hiring senior technical talent, defining career paths, supporting performance development, and fostering continuous learning.
  • Provide technical leadership through architecture reviews, code reviews, technical problem-solving, and governance design decisions.
  • Drive adoption of governed data products and self-service access models across internal teams and data domains.
  • Partner with Data Engineering, Security, Finance, AI/ML, and business stakeholders to ensure governance priorities align with broader technology and organizational objectives.
  • Establish scalable governance practices that can support increasing data consumption and organizational growth while maintaining strong security and compliance guardrails.

  Requirements:

  • 8+ years of experience in data governance, data platform operations, data management, or a closely related discipline, including 3+ years in people leadership or a senior technical leadership role.
  • Demonstrated experience building and scaling enterprise governance programs in cloud environments such as AWS, Azure, or GCP.
  • Proven ability to hire, mentor, develop, and lead technical teams, with experience in performance management and organizational development.
  • Deep knowledge of Snowflake architecture and governance, including RBAC design, functional and access roles, row-level security, data masking, network and authentication policies, resource optimization, and cost controls.
  • Strong AWS expertise, including S3, IAM, governance integrations, and multi-engine data architectures involving technologies such as Iceberg, Athena, and Spark.
  • Enterprise compliance experience with SOX, SOC 2, or equivalent frameworks, including access controls, audit evidence, segregation of duties, and continuous compliance automation.
  • Strong understanding of data catalogs and metadata management platforms such as Alation, Collibra, or comparable technologies, including lineage, PII tagging, and stewardship models.
  • Knowledge of modern data platforms such as Databricks and their governance capabilities, including cataloging, lineage, and access control.
  • Experience with Snowflake AI/ML capabilities such as Cortex, Agents, and Snowpark ML, and an understanding of governance requirements for AI data pipelines.
  • Experience with platform economics, including cost attribution, chargeback models, resource optimization, and ROI measurement for data-platform investments.
  • Familiarity with Terraform or comparable Infrastructure-as-Code technologies for governance automation and policy enforcement.
  • Experience operating in enterprise SaaS or similarly distributed environments with decentralized data ownership, self-service models, and rapid organizational scaling is preferred.
  • Strong strategic thinking, stakeholder-management, communication, and influencing skills, with the ability to balance governance, business enablement, security, and innovation.
  • Servant-leadership mindset with a strong focus on mentoring, collaboration, empathy, and developing technical talent.

  Benefits:

  • Flexible-first working environment with remote and hybrid ways of working.
  • Opportunity to lead enterprise-scale data governance and platform initiatives supporting thousands of data consumers.
  • Exposure to modern technologies across Snowflake, AWS, Databricks, Iceberg, AI/ML, and cloud data platforms.
  • Opportunities to shape AI/ML governance and responsible data practices as emerging technologies evolve.
  • Professional growth through mentorship, learning programs, leadership development, and education support.
  • Opportunity to hire, develop, and grow a high-performing technical governance organization.
  • Paid volunteer time and company-wide initiatives designed to support time for recharge and community involvement.
  • Well-being resources and regionally tailored programs supporting employees and their families.
  • Opportunity to work within a global, flexible-first technology culture focused on innovation, collaboration, and continuous improvement.
  • Significant strategic influence over platform architecture, governance maturity, cost efficiency, and enterprise data culture.