Smart Data Databricks Partnership Announcement
May 28, 2026 – We are now an official Databricks partner.
The partnership puts a formal name on work our team has been delivering for a while. We have been embedded with a Fortune 100 grocer, helping move their data platform onto Databricks at enterprise scale. That engagement is what brought our Databricks practice to a place where the partnership made sense.
Why this matters for the people we work with
Becoming a Databricks partner does a few practical things for the customers and prospects we talk to every week.
It signals that our Databricks delivery muscle is real, not a side practice. The team running this work has been in production Databricks environments, not lab projects. The partnership reflects that, and it gives our customers the assurance that the Databricks ecosystem has reviewed and accepted us.
It opens up direct enablement and partner-resource access. We work from current product information, certification paths, and partner-portal resources rather than what was on the marketing site six months ago. That feeds back into the recommendations we make. When a customer is choosing between platforms, or sequencing a migration, we are working from current information.
It gives us a formal line to the Databricks ecosystem when it matters. Technical questions, architecture validations, and ecosystem orientation move faster when there is a partner relationship behind them.
Where we focus on Databricks
The work we are doing today, and the work we expect to grow into through the partnership, sits in a few places.
Legacy data platform migration to Databricks. Enterprise legacy ETL stacks and orchestration tooling moved onto Databricks pipelines, asset bundles, and modern scheduling. This is where the bulk of our recent Databricks delivery has been concentrated.
Cloud-native data delivery. Production pipelines, validation frameworks, shared services, and reusable libraries that hold up under enterprise load. The parts that get glossed over in vendor demos.
AI-assisted modernization. We have been applying AI tooling to accelerate legacy translation work where it makes sense, and the partnership puts us closer to where that conversation is happening on the platform itself.
What comes next
This is the start of the formal relationship, not the finish. We will share more on what the partnership unlocks for our customers as the joint roadmap firms up. If you are evaluating Databricks for your data platform, or working through a legacy migration onto it, we would welcome the conversation.
Contact us to learn more about how we can support your Databricks roadmap.
