Product Expert at Datafold (S20)
$120k - $180k  •  0.07% - 0.07%
Deal with analytical data quality in the pull request
Remote
Full-time
1+ years
About Datafold

Datafold exists to make working with data more enjoyable and productive.

We are all about empowering data and analytics engineers. We find the most tedious, error-prone, and repetitive tasks and create tools to automate them. We make the world better by giving superpowers to data professionals who solve hard problems in various domains with data.

We are fully remote and a highly technical team with deep expertise in the data domain. To date, Datafold raised $22M from top-tier investors, including YCombinator, NEA & Amplify Partners.

Now is a unique time to join our fully remote team: with solid momentum behind, there is yet so much ahead with an opportunity for every team member to shape our product, business, and culture.

About the role
Skills: Python, SQL, Data Analytics

Datafold exists to make working with data more enjoyable and productive.

We are all about empowering data and analytics engineers. We find the most tedious, error-prone, and repetitive tasks and create tools to automate them. We make the world better by giving superpowers to data professionals who solve hard problems in various domains with data.

We are fully remote and a highly technical team with deep expertise in the data domain. To date, Datafold raised $22M from top-tier investors, including YCombinator, NEA & Amplify Partners.

Now is a unique time to join our fully remote team: with solid momentum behind, there is yet so much ahead with an opportunity for every team member to shape our product, business, and culture.

We are looking for a Product Expert to assist our customers on their journey to do data better with the Datafold platform. Relying on your expertise in Data/Analytics Engineering, as well as incredible empathy and communication skills, you will play a central role in connecting the dots between our current and prospective customers and internal Engineering and Business teams. You will help our customers extract the full value of the Datafold platform, assist in resolving their challenges and channel the user feedback back to the internal teams.

An ideal candidate for the role is an experienced Data/Analytics Engineer passionate about finding ways to do data better through building valuable tools and sharing knowledge to empower others.

In this role you will:

  • Own and edit Datafold’s technical content, including technical blog articles, product documentation, and changelog
  • Host training sessions and educational webinars for current and prospective users-
  • Participate in conversations with potential customers to educate them about the capabilities of the Datafold platform and help assess the solution fit
  • Engage with our current and prospective users across various channels, including Slack and in-app chat, to answer their questions and provide first-line support
  • Help Sales and Marketing teams understand the capabilities of the Datafold platform in the context of - -
  • Data/Analytics Engineering workflows and challenges
  • Synthesize and communicate feedback from customers and the data community to the Product, Engineering & Design teams

What we value:

  • Substantial hand-on Data/Analytics Engineering experience on Modern Data Stack
  • Expert-level knowledge of SQL; Working knowledge of Python
  • Exceptional communication and writing skills
  • Stellar portfolio of technical content such as blog posts, docs, talks
  • Proven ability to effectively work in fast-past environments

You'll be an exceptional fit if you

  • Worked with modern analytics engineering tools such as dbt and Dagster
  • Have software development experience in Python
  • Made contributions to open-source software
Technology

Datafold is a distributed web application with a rich interactive UI. Our backend is primarily written in Python with the use of FastAPI, SQLAlchemy, and Celery. We rely on Rust for specialized and performance-critical components. The data is stored in PostgreSQL, Neo4j (metadata graph), and Clickhouse (logs and time series). Our frontend is written in Typescript with the use of React, Redux, and GraphQL. We also use WebAssembly for performance-critical components.

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