Matillion Transforms Complex Data Work With The Industry’s First AI-Powered Data Engineer

Data engineering is time consuming, complex and repetitive. Bottlenecks and delays are common as engineers face ever-increasing backlogs of tasks. And in an age where data fuels every decision, any delay in time to insight can have serious impacts on organizational success. 

Matillion is changing this reality by streamlining and automating data engineering workloads, allowing users to do more with smaller teams. Its intelligent data integration platform enables users to rapidly build and manage pipelines — so people can spend less time wrangling technology and more time doing the AI and analytics work that adds value to the business. 

The company’s new AI tool, Maia, is a team of agentic data engineers, created to autonomously design, build, optimize and maintain pipelines, accelerating outcomes and lowering cost. And it’s all been built on Snowflake’s AI Data Cloud.

As organizations expand AI production use cases, being able to move, transform and make data AI-ready at speed and scale is crucial. Matillion has created a transformative new tool to meet this need.

Maia is an AI agent that allows users to load, transform and move data to Snowflake using natural language requests. It doesn’t just interpret those requests; it turns them into production-ready pipelines to accelerate the delivery of trusted data. 

By automating ingestion, transformation, orchestration, testing and deployment, it allows non-experts to build the pipelines they need — and enables data teams to save weeks of effort.

Maia ensures pipelines stay current and healthy, flags anomalies and errors, and even plays the role of a data architect to scale governance and structures to meet growing demand. The result: smaller teams can do far more, redirecting data engineers from repetitive work to high-value innovation.

Matillion calls it “a data engineer in your pocket.” The result is a true transformation in data engineering work that could see companies restrategize their approaches. 

“With Maia you can ask questions of your data, and it will produce results on the spot,” says Jean Mandarin, Senior Manager of Data Insights at Matillion. “Through handling ingestion, transformation, orchestration and testing, it allows non-experts to build the pipelines they need and makes data teams more productive — especially smaller teams.”  

As a long-term Snowflake partner, using the AI Data Cloud to bring Maia to life was the obvious choice for Mandarin and his team. Matillion was able to use Snowflake’s governance, security and compute power in its proprietary product, along with out-of-the-box Cortex AI functionality.

“Snowflake provides a whole suite of AI features that Maia uses, such as Cortex Sentiment,” says Mandarin. “The AI Data Cloud is AI-ready, which means that any AI tool you want to build will work really nicely within the platform.”

As well as using Snowflake as a development platform for Maia, Matillion has transferred its own data estate to Snowflake’s AI Data Cloud, looking to add scalability, speed and security to support the company’s growth.

“We moved to Snowflake for its unified storage and compute,” says Mandarin. “We needed a tool where we could easily store, manage and process data straight away and we knew that the robustness of its architecture was better than the competitors.” 

The company’s multiple Snowflake accounts serve departments across the organization, from sales and finance to product development and engineering. And Mandarin has seen some huge advantages related to costs and productivity. 

“Previously, we needed a team to look after our architecture, and it required a dedicated and specialist resource,” he says. “With Snowflake, we no longer need that. There’s no bottleneck anymore and it’s a huge cost saving.” 

One of the biggest advantages is the way Snowflake enables self-service analytics at scale.

Moving away from traditional business intelligence tools, Matillion now uses Snowflake Intelligence to provide on-demand insights to non-technical users through natural language queries. 

With an interface accessible through Slack, one of the most commonly used tools among employees, there’s no barrier to entry or new tools to learn — just an easier way to interrogate data from a familiar workspace. But it’s not just about putting data in the hands of more people. It’s also about the depths of the insights. 

“Before you could look at some data, but if you wanted to know why something happened you’d have to put a request in with the data team to explore it,” Mandarin says. “With Snowflake Intelligence, you can simply ask that question, and go on to ask what your recommended next actions should be. It’s a real game changer.” 

Matillion uses Snowflake Intelligence for a range of use cases, including comparing usage patterns across segments without waiting on analysts, and surfacing upsell opportunities by analyzing customer consumption data. The result is the equivalent saving of one full-time analyst. 

Matillion is an example of what the future of data work may look like. With Maia, the company has a digital engineer on demand, and with Snowflake Intelligence it also has a data analyst. It’s an automated workflow that covers almost all touchpoints, and the potential is limitless. 

“With these two capabilities, you have a completely scalable, end-to-end AI data platform — so you can say goodbye to bottlenecks,” says Mandarin. “It’s like having a Chatbot specifically focused on your data. There’s no turnaround time, you don’t have to raise a request, and with the right people asking the right questions, they’re going to find areas of insight we’ve never even thought of.”

Imagination is the only limit for these AI-augmented data use cases. Matillion is eager to continue its partnership with Snowflake and discover what else is possible to help its internal teams and customers put their data to work. It now plans to explore what other agentic AI apps it can build within the Snowflake framework to further automate data workflows — and put trusted data into the hands of those who need it.