ABOUT SID

Data Buddha || Cloud AI Solutions & Products Expert || AI/ML, GTM, TAM Modelling Guru || 

Chief Revenue/Data Officer || Storyteller

I specialize in helping organizations operationalize AI through scalable data foundations, cloud infrastructure, and enterprise workflow transformation.

Over the past 6+ years, I have worked across startup, high-growth, and enterprise environments helping organizations modernize their go-to-market, customer intelligence, and AI operational ecosystems using platforms such as Snowflake, Databricks, AWS, Azure, Google BigQuery, Salesforce, HubSpot, Marketo, and ZoomInfo.

My experience spans enterprise solutioning, AI workflow enablement, data modeling, GTM architecture, cloud data infrastructure, and AI agent implementation across more than 1,000 enterprise customer engagements. I focus on bridging the gap between fragmented operational systems and production-ready AI environments that improve business efficiency, accelerate decision-making, reduce operational friction, and enable scalable internal AI adoption.

I have led and supported initiatives involving:
• Enterprise data foundation modernization
• AI agent and internal AI workflow development
• Snowflake and Databricks query automation
• Customer intelligence and data orchestration
• GTM and ABM infrastructure strategy
• LTV, ICP, segmentation, and territory modeling
• AI-assisted operational workflows
• Cloud-native data architecture
• Revenue Operations transformation
• Cross-functional AI enablement initiatives

At ZoomInfo, I helped build internal AI agent workflows and AI-powered operational systems that improved productivity for Sales and Solutions organizations. I also worked on automating Snowflake and Databricks data extraction workflows triggered through Salesforce operational processes, reducing enterprise customer turnaround times from multiple days to only a few hours while reducing manual operational overhead.

I have extensive experience helping organizations understand how to structure and centralize their customer, operational, product, and GTM data into unified data foundation layers that can support scalable AI use cases, internal copilots, agentic workflows, and enterprise decision-making systems.

My technical and strategic experience includes working with:
• Snowflake
• Databricks
• AWS
• Azure
• Google BigQuery
• Salesforce ecosystem
• Kubernetes and cloud-native workflows
• AI infrastructure and inference concepts
• Data modeling and orchestration
• AI workflow automation
• Enterprise SaaS ecosystems
• GTM and RevOps systems

At RingLead, prior to its acquisition by ZoomInfo, I helped support GTM and operational scaling initiatives that contributed to significant revenue growth from $8M to $20M and supported the company's successful acquisition. This experience provided firsthand exposure to startup scaling, M&A integration, enterprise operational maturity, and cross-functional execution across both startup and enterprise environments.

In addition to enterprise data strategy and AI workflow implementation, I have led and supported multiple operational and compliance initiatives involving ISO Certifications, SOC2 Type 2, GDPR, CCPA, and penetration testing projects. My ability to operate across technical, operational, security, and business functions has enabled organizations to modernize their infrastructure while maintaining enterprise-grade governance, scalability, and customer trust.

My philosophy is centered around a simple idea:
AI is only as powerful as the operational data infrastructure behind it.

The organizations that will win in the next generation of AI are the ones that can successfully combine people, process, data, infrastructure, and AI workflows into scalable operational systems that create measurable business outcomes.