Certified Snowflake team, on demand

Our Platform Team as a Service gives you Snowflake experts at lower cost with no hiring, no firing, no knowledge gap. Just a reliable team that keeps your data platform steady and delivers insights when you need them.

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Solution

Fast track to a high-performing data team

Scaling data teams isn’t easy. Recruiting is slow, costs keep climbing, and in-house capacity often falls behind growing data demands, feature rollouts, and governance requirements. The result? Delays, risks, and missed opportunities. With our Platform Team as a Service, you don’t need to build a large in-house department. Instead, you get immediate access to a squad of certified Snowflake engineers and architects who work directly in your workflows.

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Features

Optimized and governed, always

Eliminate the risks of a slowing platform and compliance gaps. Our certified Snowflake experts provide continuous monitoring, proactive tuning, and governance with RBAC policies and data flow tracking to keep your platform secure and efficient.

The right skills, right on time

Scale your Snowflake team as business needs change. Handle spikes in demand, accelerate new initiatives, and manage seasonal workloads with expert capacity that adjusts as needed. You always have the right skills at the right time without the risk of overhead of permanent hires.

Benefits

Why data leaders choose our Platform Team as a Service

Cost-effective expertise

Save more with Snowflake specialists shared efficiently across clients.

Flexible on-demand experts

Scale resources for spikes, initiatives, or workloads without hiring overhead.

Best Snowflake practices

Benefit from Snowflake practices that cut costs and improve performance.

Always Project Ready

You gain team ready for any data challenges and implementations.

Transparent and proven methodology

The expert-led delivery framework

No big bang. No black boxes. Our signature transparent methodology, refined through years of Snowflake experience, coordinated to deliver fast, high-quality results.

Sucess stories

How we transform data operations

Case study
5 min read

How a top global logistics leader boosted BI performance by 65% with Snowflake

One wrong move during their Snowflake migration could have brought down hundreds of BI applications and reports. With legacy systems built over 15 years and rising maintenance costs putting operations at risk, this top-5 global logistics company faced its most critical data challenge yet.

One wrong move during their Snowflake migration could have brought down hundreds of BI applications and reports. With legacy systems built over 15 years and rising maintenance costs putting operations at risk, this top-5 global logistics company faced its most critical data challenge yet.

Our experts at Snowstack stepped in to navigate this complex transformation. The outcome? A smooth migration that turned the company’s greatest risk into a long-term competitive advantage.

Key outcomes:

  • Report performance improved by 65%, with dashboards running in minutes instead of hours.
  • Infrastructure costs fell by 40% while system performance increased.
  • The migration achieved zero disruption, maintaining 100% uptime.
  • Over 65% of legacy SQL was converted automatically, saving months of effort.
  • More than 40 developers were trained and upskilled on Snowflake.
Over the years, our BI teams developed an effective approach to data modeling, which had long been a strength. However, with the ongoing migration of the central data warehouse to Snowflake, we knew that adopting new tools could take months, if not years. We urgently needed support from Snowflake professionals to guide the adoption process and help our BI teams incorporate the new technology into their workflows.                                                           - Lead Data Architect

Client overview

The client operates as one of the top 5 key players in the industry, managing supply chains that span multiple continents and serve millions of customers worldwide. Their data ecosystem had evolved organically, supporting hundreds of BI applications that power everything from real-time shipment tracking to route optimization algorithms.

The client’s BI reports weren't just internal dashboard. They powered customer-facing systems that enterprise clients used to track shipments worth millions of dollars. Any disruption to these systems could trigger contract penalties and damage relationships with major accounts.

The challenge

15 years of business growth had created a BI environment that was difficult to manage. Hundreds of reports were built independently by different teams with varying skill levels. Although they all drew from the same data warehouse, each team applied its own transformation logic within separate BI systems. What began as team-specific solutions had grown into a web of technical debt that no one fully understood.

Our solution

Recognizing the critical need for modernization, the client made the strategic decision to unify their data model and move it to Snowflake alongside their ongoing data warehouse migration. We guided the client through five steps.

Step 1: identifying the foundation

Together with the client, we analysed their extensive BI landscape to identify the datasets most frequently used across reports. This joint assessment defined a minimum viable product (MVP) scope that would deliver immediate value and build momentum for the broader transformation.

Step 2: building the Snowflake environment

We worked with the client to establish a dedicated Snowflake environment designed specifically for BI collaboration. Together, we implemented:

  • Standardized schemas and roles to ensure consistent data access patterns across teams
  • Compute scaling strategies optimized for BI workloads
  • Role-based access control (RBAC) to strengthen governance
  • BI-specific access patterns tailored to Snowflake datasets

Step 3: automating the migration process

To accelerate the transition and protect prior investments, we partnered with the client to implement automated migration scripts that converted legacy SQL into Snowflake SQL. This achieved a 65% automatic refactor success rate, dramatically reducing manual work while preserving business logic.

Step 4: orchestrating seamless integration

In close collaboration, we designed and deployed new orchestration pipelines that synchronized Snowflake model builds with BI report refreshes. These pipelines were integrated with the client’s existing technology stack, including:

  • Airflow Snowflake Operator for workflow management
  • AWS SNS for notifications
  • AWS S3 for data staging
  • Git for version control

Step 5: investing in the team

Recognizing that technology transformation must go hand-in-hand with people transformation, we partnered with the client to deliver training for more than 40 BI developers. This knowledge transfer ensured teams could confidently work with Snowflake as their new backend, embedding long-term value into the organization.

Foundation for Future Innovation

Still running hundreds of disconnected BI reports with inconsistent data models?

Upgrading your BI architecture is no longer a matter of if. The real question is how quickly you can create a one source of truth before competitors pull so far ahead you can’t catch up. The companies winning today are those replacing broken reporting with accurate, unified data that every team can trust. Each month you delay, they improve decision accuracy and grow their market share.

We help you close that gap fast. Our Snowflake-certified experts bring years of experience and a proven approach to modern BI transformation. We can take years of messy, disconnected systems and turn them into a single, reliable analytics platform in months. With one source of truth in place, your teams spend less time fixing reports, more time acting on accurate information, and deliver faster business decisions.

Ready to unify your BI architecture on Snowflake?

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Project details:

  • Industry: Global Logistics & Supply Chain
  • Duration: 3 months implementation
  • Engagement Model: Migration service with comprehensive training & support
  • Team Composition: Lead Architect, Data Engineers, Migration Specialists, BI Developers
  • Frequently Used Snowflake Components: Warehouses, RBAC, Snowpipe, Tasks & Streams, Secure Data Sharing, Materialized Views, Time Travel, Stored Procedures
  • Other Tools Integrated: Airflow Snowflake Operator, AWS SNS, AWS S3, dbt, Fivetran, Power BI, Azure AD

Case study
5 min read

How a global finance leader achieved AI readiness in 90 days with Snowstack

Monthly spend had passed $800K with no clear breakdown of where the money was going. By partnering with us, they gained full visibility and, within 90 days, turned uncontrolled costs into a governed, AI-ready platform built for scale.

$800K in cloud costs every month, and no explanation. For a leading financial services firm, cloud was critical to scaling the business, yet it had become one of the fastest-growing expenses. Monthly spend had passed $800K with no clear breakdown of where the money was going. By partnering with us, they gained full visibility and, within 90 days, turned uncontrolled costs into a governed, AI-ready platform built for scale.

Key outcomes:

  • Data ingestion latency reduced by 80%
  • AI-readiness achieved in 90 days
  • Real-time cost monitoring and automated optimization
  • Modern data platform for analytics, ML, and AI use cases

Client overview

Our client is a financial services company generating $500M in annual revenue with a team of 2,500 employees across North America and Europe. In the midst of rapid growth, they were transitioning from legacy systems to a modern cloud data platform built on Snowflake. But they faced rising cloud costs and a fragmented data landscape.

The challenge

Our client had ambitious AI and GenAI goals, but lacked the foundational architecture to support them cost-effectively.

The client knew what Snowflake could deliver but needed the right partner to design, implement, and operationalize a solution that would translate that capability into measurable business value.

Our solution

The client set out to gain full visibility, governance, and scalability in their cloud environment. By partnering with us, they implemented a modern, AI-ready data platform built on Snowflake to address the challenges limiting performance.

Unified data Ingestion with OpenFlow

They consolidated structured and unstructured data from SharePoint, Salesforce, and custom systems into a single ingestion framework, eliminating fragmented pipelines and enabling real-time analytics.

Centralized Metadata and governance with Horizon Catalog

They integrated metadata from BI tools, dbt models, and Iceberg tables into one governed repository, achieving full lineage visibility, consistent KPIs, and stronger compliance controls.

Consistent logic with semantic views

Business rules were embedded directly into the data layer. This made sure that every team worked from the same definitions for analytics and AI training.

Self-service analytics with Cortex AI SQL

Business users can now query governed datasets in natural language, reducing reliance on engineering and accelerating decision-making.

FinOps cost governance

Daily cost visibility, clear ownership tracking, and accurate forecasting were integrated into operations, turning cost control into a proactive practice.

Why it mattered

If you can’t see your cloud costs, you’re losing money. In many enterprises, unused services, duplicate workloads, and unclear cost ownership quietly drain millions each year. Without visibility and governance, budgets overspend, AI projects stall, and growth slows.

Our team provides the insight and control to stop waste, making every cloud dollar accountable and directly tied to business results. So start controlling your cloud spend today.

Book a Snowflake consultation.

Project details:

  • Industry: Financial Services
  • Duration: 90 days (initial build) + ongoing support
  • Engagement Model: FinOps & AI readiness program
  • Team Composition: Snowflake Solution Architect, Data Engineers, BI Specialist, Data Governance Lead
  • Frequently Used Snowflake Components: OpenFlow, Horizon Catalog, Cortex AI SQL, Semantic Views
  • Other Tools Integrated: SharePoint, Salesforce, dbt, Fivetran, Power BI

From 80% faster reporting to 65% cost savings, here's how our clients turned data into business results.

View all stories

Enterprise-grade security

Enterprise security controls and governance frameworks built into every Snowflake implementation. Role-based access, data encryption, and audit trails configured from day one.

SOC 2
Compliance

Testimonials

What our clients say

What used to take us hours of manual clean-up across dozens of Excel files is now a seamless process. The Snowstack team didn't just give us technology – they gave us our time back. We now build better reports much faster, and can finally think about predictive analytics as a reality, not just a wish. They felt like part of our team from day one.

Head of Sales Intelligence

Having a dedicated Snowflake team that truly understands our platform made all the difference. We no longer chase incidents or firefight pipeline issues – we’re focused on enabling the business. Their ownership, responsiveness, and expertise elevated our data platform from a bottleneck to a strategic asset.

Senior Director, Data Platforms

Working with Snowstack was a game-changer. Their team came in with a clear methodology, deep Snowflake expertise, and zero handholding needed. We didn't have to move a muscle in-house – they brought it all, tailored it to our business, and delivered fast.

CTO, Regional Pharma Distributor

Over the years, our BI teams developed an effective approach to data modelling, which had long been a strength. However, with the ongoing migration of the central data warehouse to Snowflake, we knew that adopting new tools could take months, if not years. We urgently needed support from Snowflake professionals to guide the adoption process and help our BI teams incorporate the new technology into their workflows.

Lead Data Architect

FAQs

Find answers to frequently asked questions about our Snowflake implementation services.

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What is Platform Team as a Service and how does it work?

Platform Team as a Service provides a dedicated group of Snowflake-certified experts who keep your data platform running smoothly. They maintain performance, support data consumers, integrate new sources, deliver improvement projects, and manage migrations, ensuring your Snowflake environment stays reliable, efficient, and ready for AI.

How does Platform as a Service differ from hiring an in-house engineering team?

Building an internal team is time-consuming, often taking months to recruit and onboard. With Platform Team as a Service, you get instant capacity from engineers who have already delivered enterprise-grade Snowflake projects across industries like finance, pharma, and FMCG. The model reduces risk, accelerates time-to-value, and delivers predictable outcomes without long hiring cycles.

What problems does Platform Team as a Service solve?

Many companies struggle with siloed systems, slow queries, high Snowflake costs, and a lack of engineering bandwidth. Our platform teams solve these by delivering governed architectures, automated data pipelines, and cost-controlled warehouses. The result: faster analytics, secure compliance (SOC2, HIPAA, PII), and an AI-ready platform that scales with your business.

How quickly can Platform Team as a Service deliver results?

Most our engagements deliver production-ready environments in as little as three months. Early wins such as automated reporting, faster dashboards and measurable cost savings often appear within weeks. Our accelerators and delivery frameworks ensure we move fast while maintaining precision and compliance.

Can Platform Team as a Service prepare our Snowflake platform for AI?

Yes. Most AI initiatives fail because the underlying data is fragmented or ungoverned. Platform Team as a Service focuses on building clean, structured, and trusted data foundations. We integrate Snowflake capabilities like Snowpark, Semantic Views, and Cortex AI SQL to prepare your organization for predictive analytics and generative AI workloads.

What does the Platform Team composition look like?

A Platform Team as a Service engagement follows our Wolfpack methodology. Each project has a lead architect setting the route, supported by data engineers and governance specialists who keep the platform steady. Additional experts such as FinOps, AI or compliance join the pack at the right moments, so the team stays aligned, adaptive, and always focused on reaching the destination.

How does Platform Team as a Service reduce Snowflake costs?

Our engineers apply FinOps best practices such as warehouse right-sizing, auto-suspend tuning, and workload optimization. By monitoring usage patterns and catching runaway queries, Platform Teams routinely reduce Snowflake costs by 30–50% while improving performance across reporting and analytics workloads.

Still have questions?
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Ready to Transform Your Data?

Contact us today to discuss how our Snowflake implementation can elevate your business operations.

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