Data Engineer, Datafold

Migrations

Salary not provided

SQL

Airflow

Snowflake

BigQuery

Oracle

SAP

dbt

Senior and Expert level

Remote from US

Quality assurance & monitoring platform for data engineers

Open for applications

Quality assurance & monitoring platform for data engineers

21-100 employees

B2BData storageEnterpriseSaaSData Analysis

Open for applications

Salary not provided

SQL

Airflow

Snowflake

BigQuery

Oracle

SAP

dbt

Senior and Expert level

Remote from US

21-100 employees

B2BData storageEnterpriseSaaSData Analysis

Company mission

To ensure that no data engineer faces sleepless nights worrying about a hotfix that broke the data or cost their company millions.

Job

Company

Role

Who you are

5+ years of experience as a Data Engineer
Advanced mastery of SQL
Strong understanding of key data engineering patterns, including batch orchestration (Airflow, dbt, Dagster, etc.) and streaming pipelines
Outstanding communication skills (consulting or customer-facing experience is a plus)
Familiarity with at least one legacy (Oracle, SQL Server, SAP HANA, Teradata, etc.) or modern (Snowflake, Databricks, BigQuery) data stack, with the ability to quickly learn and understand the use, purpose, and key differences of these systems

Desirable

Driving data platform migrations
Across a broad set of data tools, including BI, (reverse) ETL, orchestration, etc

What the job involves

We are looking for a Data Engineer to play a key role in strategic customer engagements, leveraging the Datafold Migration Agent (DMA)—an AI-powered tool that’s transforming data migration
You will be instrumental in accelerating workflow migrations, helping customers transition their data platforms in a fraction of the time and cost
Meet with the customer and create an in-depth understanding of their migration project and architecture
Collaborate closely with Datafold’s Engineering team on assembling an AI migration pipeline
Advise the customer and Datafold team on the best way to approach migrations
Leverage Datafold’s AI migration toolkit to perform translation and validation of complex pipelines

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

Company

Funding (last 2 of 3 rounds)

Nov 2021

$20m

SERIES A

Nov 2020

$2.1m

SEED

Total funding: $22.3m

Company benefits

Unlimited PTO
Co-working budget
Home office budget
Flexible working hours
Parental leave

Company HQ

Chelsea, New York, NY

Leadership

Gleb Mezhanskiy

(CEO & Founder)

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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