Full-Time

Enterprise Account Executive

Confirmed live in the last 24 hours

Dagster Labs

Dagster Labs

11-50 employees

Data orchestration platform for productivity

Data & Analytics
Enterprise Software

Compensation Overview

$300kAnnually

Mid, Senior

Remote in USA

Candidates must be authorized to work within the United States.

Category
Strategic Account Management
Sales & Account Management

You match the following Dagster Labs's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • A minimum of 2-4 years of SaaS sales experience. Data orchestration experience is strongly preferred
  • A strong sense of urgency and motivation to exceed aggressive sales goals
  • Interest in boosting your technical skills. You won’t need to read server logs coming in, but you should be open to learning the fundamentals
  • To be both flexible and coachable. We will be fine-tuning our sales approach as we go along, and we expect you to do the same
  • Excellent communication and interpersonal skills
Responsibilities
  • Identify outbound opportunities and qualify inbound leads
  • Help refine the sales process and strategy to improve your effectiveness
  • Own the entire sales process, including product presentations, account management, generating quotes, negotiating contracts, and closing business
  • In collaboration with the CSM, maintain the new customer relationship through the first renewal to increase account ARR.
  • Communicate cross-functionally with our support, product, and development teams

Dagster Labs develops a data orchestration platform called Dagster, which is designed to enhance productivity in managing data workflows. The platform allows users to define, schedule, and monitor data pipelines, making it easier to handle complex data processes. Unlike many other data orchestration tools, Dagster focuses on providing a clear structure for data workflows, enabling teams to collaborate more effectively and maintain better visibility into their data operations. The goal of Dagster Labs is to streamline data management, helping organizations to work more efficiently with their data.

Company Size

11-50

Company Stage

Series B

Total Funding

$78.6M

Headquarters

San Francisco, California

Founded

2018

Simplify Jobs

Simplify's Take

What believers are saying

  • Recent $33M Series B funding boosts development and marketing efforts for Dagster.
  • Growing demand for sophisticated data orchestration tools aligns with Dagster's offerings.
  • Dagster's platform supports critical decision-making processes, increasing its market relevance.

What critics are saying

  • Competition from Treeverse's lakeFS 1.0 may challenge Dagster's market position.
  • Focus on GitHub stars could divert attention from essential product development.
  • Rapid tech evolution in data orchestration may risk Dagster's obsolescence.

What makes Dagster Labs unique

  • Dagster Labs offers an open-source orchestration platform for data asset management.
  • The platform is designed for productivity, scalability, and observability of data assets.
  • Dagster's integration with lakeFS enhances data version control capabilities.

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Benefits

Flexible Work Hours

Remote Work Options

Company News

VentureBeat
Oct 24th, 2023
Open Source Lakefs Data Version Control Levels Up To 1.0

VentureBeat presents: AI Unleashed - An exclusive executive event for enterprise data leaders. Network and learn with industry peers. Learn More. Treeverse, creators of the open-source lakeFS data version control system, today announced the release of lakeFS 1.0. This major update brings production-level stability, security and performance to the data lake version control software.The lakeFS project got its start back in 2020 and has been steadily improving in the years since, providing an open source technology to help organizations with version control for object storage based data, stored in data lakes.Treeverse, the lead company behind the technology, raised $23 million back in 2021 to build out the concept that delivers capabilities that are similar to the open source Git version control system, to data lakes. In 2022, the technology got a cloud service with Treeverse launching the  lakeFS cloud offering providing a managed cloud service data version control

Technical.ly
Aug 9th, 2023
Should Startups Worry About Github Stars?

This is a guest post by Fraser Marlow, Elementl’s Philly-based head of marketing. In May of this year, our open-source software startup Elementl closed a successful Series B round. In the run-up to the fundraising, I spent a fair amount of time preoccupied with GitHub stars. If you are unfamiliar with these, you can think of them as the “like” button on an open-source project. When developers find a project they like, they can bookmark it with a star or simply “star” the repo as a general vote of appreciation

TechCrunch
May 24th, 2023
Elementl Raises $33M Series B For Its Data Orchestration Platform Based On Dagster

Elementl, a startup that is building a data platform based on the popular Dagster orchestrator, today announced that it has raised a $33 million Series B round led by Georgian. This round also saw participation from new investors 8VC and Human Capital, as well as existing investors Sequoia, Index, Amplify, Hanover and Slow. The new round brings the company’s total funding to $48.8 million.As is so often the case, Dagster founder Nick Schrock also founded Elementl after many years at Facebook, where he also co-created GraphQL. Schrock is currently the company’s CTO and chairman, with his former Facebook colleague Pete Hunt now the company’s CEO. As Hunt told me, he had invested in Elementl as part of its 2017 seed round — mostly as a bet on Schrock. Hunt admitted that at that point, he didn’t really understand the value proposition of Dagster but as he worked on more data problems at Facebook and then later at Smyte, the anti-abuse service he co-founded and later sold to Twitter, the need for better data orchestration quickly became clear to him.Image Credits: Elementl“I realized that there are these big complex data pipelines that are making very serious decisions — not just taking down social media posts but also deciding who gets a mortgage, all that stuff