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Datafold

Automated data quality testing platform

Forward Deployed Data Engineer

Full-Time
$155k - $200k/yr
Mid, Senior
Remote in USA
Remote
Solution EngineeringImplementation & Technical Account Management

About the job

Requirements
  • 3–6 years in data consulting, professional services, or a customer-facing data engineering role.
  • Strong grasp of the modern data stack, including dbt, Snowflake, Databricks, orchestration tools, and major patterns such as stored procedures, streaming, and incremental processing.
  • Use AI every day and continuously learn and improve how to use it effectively.
  • Identify, surface, and fix problems and rally the team to help without being told.
  • Communicate effectively in executive check-ins and technical design sessions.
Responsibilities
  • Own 1–4 concurrent migration projects end-to-end, including scoping, planning, execution, and customer handoff.
  • Serve as the primary customer contact by running weekly check-ins, managing stakeholder expectations, and escalating risks early.
  • Configure Datafold's Migration Agent and oversee migration execution.
  • Partner with Datafold's engineering team to execute migrations.
  • Help refine and scale the product and delivery playbook as the team grows.
Desired Qualifications
  • Exposure to legacy data stacks and patterns, including ETL and stored procedures.
  • Experience with data platform migration projects.

About the company

Summary of Datafold 1) What it does: Datafold is a platform for data quality that combines automated testing and observability to prevent data problems. It helps data teams make sure data is correct and reliable by catching issues before they affect the data warehouse. 2) How the product works: Datafold plugs into the data development cycle and runs automated tests during key moments—deployments, migrations, and ongoing monitoring. This setup checks data pipelines and code changes for correctness and flags issues early, so bad deployments don’t reach the warehouse. 3) How it stands out: Unlike tools that mainly detect problems after they happen, Datafold focuses on preventing issues by integrating testing into the development process. It targets data teams across industries and uses a subscription model for ongoing access. 4) The goal: To improve data integrity and development speed by stopping data quality problems before they reach production data warehouses.

Company Size

11-50

Company Stage

Early VC

Total Funding

$26.2M

Headquarters

New York City, New York

Founded

2020

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Simplify's Take

What believers are saying

  • May 2025, Datafold raised $4 million, extending runway for product expansion.
  • The September 2026 website shows integrations with Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow.
  • G2's September 2026 listing shows 4.5/5 from 24 reviews.

What critics are saying

  • Datafold discontinued active support for open-source data-diff on May 17 2024.
  • 2026 headcount sits around 34, limiting enterprise sales and support capacity.
  • Snowflake, Databricks, and dbt can bundle adjacent features and squeeze Datafold.

What makes Datafold unique

  • Datafold's CI/CD Data Diff catches value-level changes beyond schema checks.
  • It combines reconciliation, column-level lineage, and proactive monitoring in one platform.
  • Its May 11 2026 MCP exposure plugs data QA into coding agents.

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Benefits

  • Remote Work Options

Growth & Insights and Company News

6 month growth

-8%

1 year growth

-8%

2 year growth

-5%
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AlleyWatch
May 29th, 2025
The AlleyWatch Startup Daily Funding Report: 5/29/2025

Datafold, an automation platform for data engineering teams, has raised $4M in funding according to a recent SEC filing.

VentureBeat
May 15th, 2023
Data Downtime Almost Doubles As Professionals Struggle With Quality Issues, Survey Finds

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Datafold
Jun 28th, 2022
Datafold launched open source package on Jun 21st 22'.

Last week Datafold launched an open source package for diffing data between databases e.g. PostgreSQL <> Snowflake.

VentureBeat
Jun 22nd, 2022
Datafold Launches Open-Source Diffing Tool To Execute Data Validation Checks

To further strengthen our commitment to providing industry-leading coverage of data technology, VentureBeat is excited to welcome Andrew Brust and Tony Baer as regular contributors. Watch for their articles in the Data Pipeline. New York-headquartered data reliability company Datafold has launched an open-source diffing tool to help enterprises compare databases and perform checks to validate data consistency