Be the one building AI-powered experiences where they matter most.

At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.

Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.

About the Role

The Manager, Data Platform Governance & Operations is the strategic and operational leader of enterprise data governance, responsible for building and scaling governance infrastructure across Snowflake, AWS, and emerging data platforms. You will lead a small, high-performing team that includes senior engineers, oversee compliance and cost strategy, and partner with platform, engineering, and business teams to enable governed, self-service data access at scale.

This role bridges governance policy, platform engineering, and organizational leadership.

You will own the vision and execution of a code-first governance discipline, establish data governance culture, manage platform economics, and lead hiring and mentorship of technical talent. Success means embedding governance as an enabler, not a blocker, across hundreds of internal and external data consumers.

Key Collaborators: Data Engineering, Data Governance, SOX, AI/ML teams

Key Responsibilities

Strategic Governance & Platform Leadership

• Define and evolve the enterprise data governance strategy, including RBAC patterns, compliance frameworks, cost optimization, and AI/ML data governance maturity roadmap
• Own the Snowflake and AWS platform governance architecture, ensuring security, compliance, cost efficiency, and self-service enablement across environments
• Partner with platform and engineering teams to embed governance capabilities (RBAC, network security, data masking, Iceberg integration) into Snowflake, AWS, Athena, and emerging platforms
• Establish governance foundations for AI/ML initiatives, including Snowflake Cortex model governance, data lineage for AI pipelines, responsible data use policies, and Snowpark ML asset management

Governance Operations & Compliance

• Operationalize enterprise data governance standards through automation, policies, and controls across Snowflake and AWS platforms
• Own SOX compliance execution, including access controls, audit evidence generation, segregation-of-duties monitoring, and continuous compliance validation
• Manage data catalog operations and metadata governance, ensuring accurate lineage, PII tagging, data masking policies, and stewardship practices across domains
• Monitor governance adherence and compliance posture through automated reporting, anomaly detection, and visibility dashboards

Platform Economics & Cost Strategy

• Own Snowflake and AWS platform cost management, including warehouse sizing strategy, compute optimization, cost attribution models, and chargeback frameworks
• Establish cost observability through resource monitors, query tagging, and governance-driven cost reduction initiatives
• Measure and report on platform ROI, governance impact (audit reduction, compliance velocity), and cost trends to leadership

Team Leadership, Hiring & Organizational Development

• Build and mentor a high-performing governance team, including hiring senior technical talent, defining career paths, and fostering a culture of continuous learning
• Partner with team members on platform architecture decisions, code reviews, and technical problem-solving
• Establish scalable governance practices that enable the team to grow from 3 to 5 engineers to support emerging organizational needs

Self-Service Enablement & Stakeholder Management

• Drive adoption of governed data products and self-service access models across the organization
• Support onboarding of new teams and data domains through standardized governance patterns and best practices
• Manage cross-functional relationships with Data Engineering, Security, Finance, and business stakeholders to ensure governance decisions align with platform roadmap and organizational priorities

What You Bring

Required Leadership Experience

• 8+ years of experience in data governance, data platform operations, or data management, with 3+ years in a people leadership or technical lead role
• Track record building and scaling governance programs in cloud-based environments (AWS, GCP, or Azure)
• Demonstrated ability to lead and mentor technical teams, with experience in hiring, performance management, and organizational development

Required Technical Expertise

• Deep knowledge of Snowflake platform architecture, including RBAC design (functional vs. access roles), row-level security, data masking, network policies, authentication policies, resource optimization, and cost controls
• AWS cloud proficiency, including S3, IAM, governance integrations, and multi-engine data architectures (Iceberg, Athena, Spark)
• Enterprise compliance experience (SOX, SOC 2, or equivalent); expertise in access controls, audit evidence, and continuous compliance automation
• Data catalog and metadata management expertise (Alation, Collibra, or similar); ability to design and oversee stewardship practices
• Knowledge of modern data platforms (Databricks) and governance capabilities such as cataloging, lineage, and access control

Preferred Expertise

• Snowflake AI/ML governance: Experience with Cortex, Agents, Snowpark ML, and establishing governance for AI data pipelines
• Platform economics: Experience with cost attribution, chargeback models, and ROI measurement for data platform investments
• Infrastructure as Code: Familiarity with Terraform or equivalent for governance automation and enforcement
• Enterprise SaaS environment: Experience in organizations with distributed data ownership, self-service models, and rapid scaling

Core Competencies

• Data Governance & Compliance Strategy
• Snowflake & AWS Platform Architecture
• Team Leadership, Hiring & Mentorship
• Data Catalog & Metadata Management
• Platform Economics & Cost Optimization
• Cross-Functional Stakeholder Management
• AI/ML Data Governance
• Servant Leadership & Organizational Development

Why You Will Succeed Here

• Lead from principles: Servant leadership and empathy matter here. You will mentor technical talent and build a collaborative governance team.
• Strategic influence: Governance decisions directly shape platform roadmap, cost efficiency, and organizational data culture.
• Emerging technology: Work with Snowflake AI, multi-engine architectures, and data platforms at the frontier of innovation.
• Scaling impact: Build governance infrastructure that serves thousands of internal and external data consumers.
• Organizational growth: Hire, mentor, and grow the team as governance maturity and adoption expand.

Business Impact

• Transforms governance from manual, audit-driven practice to a scalable, code-first discipline that reduces risk and accelerates innovation
• Reduces security, compliance, and cost risks through standardized governance controls, continuous validation, and cost transparency
• Enables self-service data access with built-in controls, accelerating analytics and AI initiatives while maintaining security guardrails
• • Optimizes platform economics through cost controls, resource efficiency, and data-driven investment decisions

#LI-GR1
#LI-Hybrid
#LI-Remote

Working at Genesys

• AI at enterprise scale – Build, support and operate AI-powered technology used by more than 8,000 organizations worldwide. 150+ new AI features were released in the last fiscal year.
• A flexible-first culture – Join a global team of nearly 7,000 employees with flexible ways of working designed to help people do their best work.
• Growth in the AI era – Build future-ready skills through mentorship, learning programs, leadership development and education support.
• Time to recharge and give back – Benefits include paid volunteer time, August Free Fridays, well-being resources and regionally tailored programs for employees and their families.
• Recognized globally – Genesys is Great Place to Work® certified in 17 countries and 94% of employees are proud to tell others they work at Genesys.

Learn more about our culture, AI innovation and sustainability commitments through our Careers site and Sustainability Report.

What Happens After You Apply

After you apply, here's what you can typically expect:

• Our Talent Acquisition team reviews your application with the hiring team.

• A Talent Acquisition Partner will review your application and, if your background is aligned, schedule a Zoom interview.


• Next, you'll meet the hiring manager and other members of the interview team.

• We aim to keep the process focused and respectful of your time, with no more than five interviews in most cases.

• After interviews are complete, our team will follow up with the final steps.

Every application is reviewed by a person. Response times may vary by role and location, but our team will keep you informed throughout the process.

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Employee Referral

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About Genesys:

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit .

Reasonable Accommodations:

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Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.

Please note that recruiters will never ask for sensitive personal or financial information during the application phase.