Head of Data Engineering & Analytics

### Who you are
- Demonstrate 15+ years of experience in data engineering, analytics, and data science, or equivalent practical experience
- Lead teams of 50+ people in senior leadership roles, building cultures of collaboration and continuous learning
- Display hands-on experience with Snowflake and modern data pipeline technologies (required), including cloud platforms (AWS), CI/CD, DevOps/DataOps, and enterprise integrations
- Demonstrate experience building data foundations to support AI/ML initiatives, including platforms like Databricks, Snowflake AI/ML (Cortex), ML Flow, LLM-based protocols and patterns (RAG/Agentic/MCP/A2A), and vector databases (Pinecone, FAISS)
- Demonstrate ability to establish operational excellence frameworks including SLAs/SLIs, end-to-end observability, cost optimization, and key operational metrics tracking

### What the job involves
- You will build and scale the data foundation that powers Zoom's AI capabilities and business operations. By defining enterprise data strategy and leading a global team, you will enable trusted insights and innovation. This role offers the opportunity to shape how a $10B+ company leverages data to drive growth
- We deliver enterprise data platforms, analytics, and AI capabilities across Zoom. Our team partners with Product, Engineering, Finance, and Sales to enable data-driven decisions. We exist to transform data into actionable insights that fuel business growth
- Defining and executing enterprise data strategy, platform architecture, and AI enablement roadmaps aligned with business goals
- Leading a global organization of 60+ data engineers, machine learning engineers, scientists, analysts, and architects across the US and India
- Building scalable data pipelines, governance frameworks, and analytics solutions that serve as the single source of truth
- Partnering with Finance, Marketing, Sales, Product, and Engineering leaders to deliver insights, dashboards, and data products
- Enabling self-service analytics and AI/ML use cases through accessible, trusted, and secure data platforms
- Create Architect modern cloud-based data platforms using Snowflake, AWS, and data pipeline technologies
- Build data foundations that support AI and machine learning initiatives at enterprise scale
- Translate business needs into technical solutions and influence both technical and non-technical stakeholders
- Apply expertise in data governance, master data management, security, and compliance frameworks
- Use tools such as DBT, Airflow, Kafka, Databricks, FiveTran, and data quality platforms
- Work with AI/ML platforms including LLMs, vector databases, and MLOps tools
- Apply deep, hands-on experience with Snowflake and modern data pipeline technologies
- Apply Expertise across the modern data stack: Cloud databases (Snowflake, Databricks, Mongo), transformation tools (DBT, Airflow), ingestion platforms (FiveTran, Stitch, Snowpipe, Kafka, Apache Pulsar, AWS Kinesis/Firehose), orchestration (Airflow, Dagster), observability (Great Expectations, BigEye), and governance (Alation, Monte Carlo, Atlan)

### The application process
- End Date: April 17, 2026

### Benefits
- Work from home opportunities
- Retirement benefits
- My-Time-Off (MTO), an extended vacation policy
- Employee Stock Purchase Plan (ESPP) and Restricted Stock Unit (RSU) Equity Program plus Yearly stock grant for all employees
- Wellness and fitness reimbursement, wellness resources, Thrive Global wellness app, TaskHuman wellness coaching app
- Employee Assistance Program (EAP) including emotional support, financial resources and legal guidance
- Paid Parental Leave (both parents) 16 weeks paid leave (or statutory if more generous)
- Employer Matching of Charitable contributions up to $500 USD equivalent/year
- Annual Zoom Store Allowance
- Business Travel Accident Insurance