Companies that use Atlan

Source: Analysis of 100 job postings that mention Atlan

I found that Atlan buyers are predominantly senior data leaders, with Directors of Data Engineering (19%), Directors of Data Management (16%), and Directors of Analytics (9%) leading purchasing decisions. These leaders are building data governance programs from scratch or modernizing existing ones. Half of the roles (35 out of 70) are leadership positions focused on establishing data strategy, implementing governance frameworks, and scaling data platforms. Their priorities center on creating trusted data foundations that support AI initiatives, regulatory compliance, and self-service analytics.

The day-to-day users span data engineers building pipelines, analytics engineers modeling data in tools like dbt, data stewards documenting metadata and lineage, and data governance analysts enforcing quality rules. I noticed practitioners using Atlan alongside modern data stacks including Snowflake, Databricks, AWS, dbt Cloud, and visualization tools like Tableau and Power BI. They're cataloging data assets, tracking lineage, managing metadata, and enabling data discovery across enterprises.

The pain points reveal organizations struggling with data chaos and seeking to build scalable governance. Companies describe needing to "transform data chaos into clarity," establish "single source of truth" platforms, and ensure "data is accurate, compliant, trusted, and positioned as a core business asset." Multiple postings emphasize moving from fragmented systems to unified data catalogs where teams can "discover, understand, and trust" their data while supporting both regulatory requirements and AI-driven innovation.

Source: Analysis of tech stacks from 180 companies that use Atlan

I noticed that Atlan users are data-mature companies that treat their data infrastructure as a critical business asset. The combination of sophisticated data quality tools (Monte Carlo Data), enterprise security platforms (Lacework), and workflow automation (Tines) tells me these are organizations that have moved beyond basic analytics into operational data management. They're not just collecting data. They're building products and making decisions on top of it.

The pairing of Atlan with Monte Carlo Data is particularly revealing. Companies using both are serious about data reliability and have likely experienced the pain of bad data breaking downstream systems. Add Tines for automation, and I see teams that are orchestrating complex data workflows across multiple systems, probably dealing with sensitive customer information that requires careful handling. The strong presence of Qualtrics suggests these companies are combining customer experience data with operational metrics, which means they're likely in competitive markets where understanding customer sentiment drives product decisions.

My analysis shows these are growth-stage or mature companies, probably in the Series B to IPO range based on their investment in enterprise-grade infrastructure. The Docker Business adoption indicates engineering sophistication and containerized environments. These aren't small startups experimenting with data tools. They're companies where data teams have earned enough credibility to command serious budgets. They appear to be product-led organizations that use data to drive everything from feature development to customer retention.

Source: Analysis of Linkedin bios of 180 companies that use Atlan

I noticed that Atlan's customers span a remarkably diverse range of industries, but they share a common thread: they're complex operations dealing with massive amounts of data. These aren't simple businesses. I'm seeing financial services giants processing millions of transactions, healthcare organizations managing patient records at scale, global retailers coordinating vast supply chains, and technology platforms serving millions of users. What unites them is operational complexity and data intensity, whether that's LendingTree connecting consumers with 500+ partners, Datavant moving 60 million healthcare records, or CME Group operating the world's leading derivatives marketplace.

These are predominantly mature, established enterprises. I'm seeing mostly companies with 1,000+ employees, many with 5,000 to 10,000+. The funding stages tell the story: Post-IPO debt rounds, publicly traded companies, or well-established private firms. These aren't scrappy startups figuring things out. They're organizations that have already achieved significant scale and are now wrestling with the complexity that comes with it.