Software Engineer (Data Catalog & Observability Products)

New York, New York, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Software Development, Data Management, Cloud ComputingIndustries

Requirements

Candidates must have 5+ years of relevant software development experience, fluency in Python or a similar high-level programming language, and proficiency with frontend development using React. Expertise across the full software development lifecycle, experience in a high-functioning engineering organization working on B2B SaaS applications or large-scale distributed systems, strong communication skills, and proven effectiveness in team contributions are required. Nice-to-have qualifications include experience with AWS, Kubernetes, Postgres, Dagster or related data orchestrators, the Modern Data Stack, and direct user engagement for research and support.

Responsibilities

The software engineer will lead and execute product development initiatives from prototype to user adoption in collaboration with product, design, and engineering peers. They will participate in technical architecture discussions, solve difficult technical problems across the software stack, and get projects over the finish line. Additionally, they will proactively identify and address opportunities for enhancement in code quality, user experience, or performance, and lead initiatives to implement these improvements.

Skills

Software Engineering

Data Catalog

Observability

SaaS

Backend Systems

Open Source

UI Development

Distributed Systems

Monitoring

Debugging

Optimization

API Design

Error Messaging

Dagster Labs

Data orchestration platform for productivity

About Dagster Labs

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 integrate and process data from various sources. 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 processes. The goal of Dagster Labs is to streamline data management, helping organizations to work more efficiently with their data.

San Francisco, CaliforniaHeadquarters

2018Year Founded

$78.6MTotal Funding

SERIES_BCompany Stage

Data & Analytics, Enterprise SoftwareIndustries

11-50Employees

Benefits

Flexible Work Hours

Remote Work Options

Risks

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.

Differentiation

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.

Upsides

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.

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