Professional Overview
Gleb Mezhanskiy is the CEO and co-founder of Datafold, a company specializing in AI-powered automation tools for data engineering workflows, with a strong focus on proactive data quality and data platform migrations. He brings extensive expertise in data engineering, drawing on his prior experience as a founding member of the Lyft data team and data engineering roles at Autodesk. His leadership positions center on building automation platforms that alleviate the manual, error-prone aspects of data engineering, particularly around testing, migration, and observability of data.
Current Role and Company Focus
At Datafold, Gleb leads the development of a unified platform that automates critical parts of data engineering such as:
- Automated testing of data and code within CI/CD pipelines and IDEs
- Data diffing for validation and verification during data migrations
- Column-level lineage tracking to map complex data dependencies
- Anomaly detection and data monitoring for data observability
- End-to-end support for migration testing and validation of data pipelines
Datafold serves a robust client base including Patreon, Thumbtack, Substack, and AngelList. The company has successfully raised $22M in funding from YC, NEA, and Amplify Partners—a reflection of strong investor confidence and market traction.
The company culture, as articulated by Gleb, emphasizes extreme ownership, proactive bias toward action, asynchronous global collaboration, and impact-driven responsibility beyond titles.
Key Professional Experience and Insights
Prior Experience at Lyft
Gleb’s experience at Lyft is a cornerstone of his expertise:
- He was deeply involved in a high-profile, multi-year data migration project migrating from Redshift to Hive, which faced severe challenges such as:
- Scope creep caused by attempts to re-architect the data model instead of performing a simpler lift-and-shift, leading to stakeholder misalignment and delays.
- Extremely slow iteration speeds on Hive, causing debugging and validation to extend migration timelines from months to years.
- Manual verification processes requiring complex differential queries to prove data parity between systems.
- A critical realization that the choice of the migration target (Hive) was suboptimal—by the time migration concluded, Hive was outdated, making the platform effectively legacy.
- Gleb candidly described this migration experience as a "career killer" for data engineers, due to low business visibility, high risk of project delays/failures, and the tedious nature of the work overshadowing innovation efforts.
- This experience directly influenced the founding vision of Datafold to automate the majority (~99%) of manual migration effort, freeing data engineers from technical debt remediation to focus on impactful data products.
Leadership Philosophy and Product Vision
- Gleb advocates for shipping early and often, preferring iterative progress over perfection.
- He believes in embedding data quality tooling directly into existing workflows to prevent errors before code deployment, reflecting a shift-left testing philosophy.
- Emphasizes the criticality of metadata completeness and accessibility to improve data engineering velocity and reliability.
- Sees automation as a transformative force in data engineering, unlocking faster migrations and accelerating time-to-impact for data teams.
- Views recruitment and team-building as equally important to product delivery, reinforcing his commitment to scale Datafold’s impact through its people.
Educational Background
- Holds a dual degree in Finance and Information Systems from Singapore Management University with study abroad experience at Carnegie Mellon University.
- Has studied economics and computer science, including completing Harvard’s CS50 online course.
- Is engaged with the data engineering community as a recognized thought leader, speaker, and podcast guest, further establishing his credibility and industry influence.
Public Presence and Thought Leadership
- Host and frequent guest on authoritative industry podcasts such as Data Engineering Podcast, Data Stack Show, and Datacast, where he shares insights on data quality, migration challenges, and the future role of AI and automation in data engineering.
- Regularly publishes expert articles, guides, and thought pieces on best practices in data migrations and data quality.
- Engaged on platforms like LinkedIn (http://www.linkedin.com/in/glebmezh) and X/Twitter (@glebmm), enabling real-time insights into his latest views and company updates.
Company and Market Position
- Datafold is positioned as a leader in data reliability engineering technology, backed by prominent investors and serving a prominent customer list.
- The platform’s integration capabilities target existing engineering workflows, reducing friction and accelerating adoption.
- The company’s recent fundraising and product expansions around AI agents, anomaly detection, and data lineage indicate a strong momentum toward becoming an essential toolset for modern data teams managing cloud migrations and agile data products.
In summary, Gleb Mezhanskiy offers a rare combination of deep technical experience in large-scale data engineering challenges, demonstrated leadership in building innovative data automation tools, and a strategic vision centered on empowering data teams to move faster and with higher confidence. His background navigating complex migrations and founding Datafold provides crucial context around the pain points his company addresses, enhancing Datafold's appeal as a transformative solution for data engineering workflows.
