Data Scientist, Datafold
Migration Intelligence
$155k
Quality assurance & monitoring platform for data engineers
Be an early applicant
Quality assurance & monitoring platform for data engineers
21-100 employees
Be an early applicant
$155k
21-100 employees
Company mission
To ensure that no data engineer faces sleepless nights worrying about a hotfix that broke the data or cost their company millions.
Role
Who you are
- Master's Degree in Data Science, Applied Mathematics, or a closely related quantitative field
- At least 2 years of previous experience in Data Science, Technology Evaluation, or Applied Analytical roles. Experience must include performance assessment of AI/ML technologies
What the job involves
- Evaluate third-party tools, platforms, and emerging technologies relevant to data migration, data infrastructure, and AI-assisted workflows, including technical benchmarking and integration feasibility analysis, and build-versus-buy assessment
- Develop and apply quantitative models and analytical frameworks to assess migration risk, predict data quality issues, and validate data consistency across source and target database environments throughout migration project delivery
- Coordinate end-to-end delivery of customer data migration projects, including scoping, sequencing, milestone planning, risk identification, dependency management, and cross-functional execution across internal teams, customers, and external partners
- Design, build, and maintain internal data pipelines and supporting infrastructure that integrate diverse structured and unstructured data sources for analytics and reporting and operational use cases
- Develop repeatable analytical playbooks, migration frameworks, and data-driven operational accelerators based on hands-on project delivery experience
- Implement data quality monitoring, automated regression validation, and lineage analysis workflows using Python and SQL to support platform development and customer migration engagements
- Evaluate cloud and multi-cloud data environments for cost efficiency, reliability, and integration risk, producing analytical recommendations that inform architectural and sourcing decisions
- Implement data models, dashboards, and internal reporting structures that unify multiple sources of information into actionable insights for product, sales, and operational teams
- Support technology partnerships and external cooperation efforts by assessing integration opportunities and coordinating the technically sound implementation of partner solutions
- Act as an internal subject matter resource for data pipeline evaluation and migration methodologies, validating analytical workflows on internal data and translating operational findings into structured product feedback
Our take
Data engineering has gone from a buzzword to a mission-critical function in a modern company - that’s resulted in a $2bn data reliability industry that will only continue to grow.
Datafold meets this pressing need with a suite of tools that tackle the most tedious, error-prone and repetitive tasks faced by data engineers. That is, unlike most existing data quality tools, Datafold catches data quality issues before they occur, not once the companies’ services have broken down.
The company is focused on expanding its toolset and enabling even more seamless integrations to onboard more customers. The goal is to be seen as part of a package alongside leading vendors like Snowflake, Databricks, bdt, etc.
Datafold’s product has received praise from enterprise leaders in this emerging field, but the company is facing competition from other venture-backed startups going after the same market. Some, from the ground up, with open-source tools like Great Expectations. Fortunately, there’s room for all to grow for now.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 4 rounds)
May 2025
$4m
EARLY VC
Nov 2021
$20m
SERIES A
Total funding: $26.3m
Company benefits
- Unlimited PTO
- Co-working budget
- Home office budget
- Flexible working hours
- Parental leave
Company HQ
Chelsea, New York, NY
Leadership
Gleb Mezhanskiy
(Founder & CEO)Data engineering veteran having been a founding member of Data teams at Autodesk & Lyft and Head of Product at Phantom Auto. Moved from Russia to earn a Master of Information Systems Management at Carnegie Mellon University.
Alex Morozov
(CTO)Held CTO positions at several startups and technology companies. Have also continuously worked as a Senior Scientist at the Russian Research Center "Kurchatov Institute" for two decades.
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