Datafold, a data reliability platform, has secured a $20M Series A investment to enhance the delivery of high-quality data products by addressing pervasive data quality issues that impede progress in the data domain. Founded by a former Lyft data engineer who witnessed firsthand the challenges of data quality, Datafold aims to address the bottleneck of manual workflows in data teams by developing tools such as Data Diff, which provides proactive data testing and detailed impact analysis for code changes. Since its inception, the company has expanded its offerings to include features like Catalog, Column-level Lineage, and Data Monitoring, supporting various workflows in data engineering. Datafold's efforts have gained traction among diverse teams, including notable early adopters like Patreon and Thumbtack. With a commitment to remote work, the company has grown from a team of three to 18 and plans to further expand with the new funding, partnering with investors like NEA and Amplify Partners. The platform's evolution is driven by a community of over 1200 members who contribute to advancing data reliability best practices.