Base Salary
$225k - $300k/yr
Responsibilities
- Build scalable, fault-tolerant ingestion systems for enterprise-scale metadata.
- Develop clean, intuitive APIs for the connector ecosystem.
- Design event-driven architectures for real-time metadata processing.
- Create schema mappings between diverse systems and DataHub’s unified model.
- Build versioning systems for AI assets including training data, model weights, and embeddings.
Requirements
- At least 4 years of experience building production-grade distributed systems.
- Advanced Python expertise with a focus on API design.
- Experience with high-scale data processing or integration frameworks.
- Strong systems knowledge and distributed architecture experience.
- A track record of solving complex technical challenges.
- Experience with DataHub or similar metadata/ETL frameworks such as Airflow, Airbyte, or dbt is a bonus.
- Open-source contributions and early-stage startup experience are bonus qualifications.
Benefits
- Hybrid work in the Bay Area with 3 days per week in the Palo Alto office.
- Equity for every employee.
- Monthly coworking stipend.
- Medical, dental, and vision coverage with 99% of employee premiums and 65% of dependent premiums covered.
- Flexible Spending Accounts and Dependent Care FSAs.
- Carrot Fertility benefits and family-forming support for all U.S. employees.
- Unlimited PTO and sick leave.
About DataHub
DataHub transforms enterprise data into trusted context, enabling intelligent decision making by humans and AI agents. As the leading context management platform built on a thriving open-source community of 15,000+ members and adopted by thousands of organizations worldwide, DataHub Cloud delivers AI-powered discovery, governance, and observability in a unified platform, ensuring that context is always relevant, reliable, and continuously refreshed across the entire data estate. DataHub is backed by Bessemer Venture Partners, LinkedIn, and 8VC. Our key differentiators: * Scalability: DataHub offers best-in-class enterprise-grade scalability in connecting to over 100 data sources, offering an embeddable connector framework, and ingesting large volumes and high velocity of metadata. * Extensibility: DataHub’s highly extensible metadata model offers easy flexibility in adapting to an organization’s unique data landscape, entities, relationships, ownership, and custom metadata descriptors. * Completeness: DataHub Cloud’s unified platform uses AI-based enhancements and automations for discovery & understanding, quality management, and collaborative governance, allowing users and AI Agents to confidently use and manage data and AI assets. * Open-Source Advantage: Customers of DataHub benefit from the joint innovation, peer support, and growing skill base of an energized community of over 15,000 DataHub practitioners. The managed service, DataHub Cloud, offers dedicated support, improved performance and availability, and secure deployment options to ease adoption across an enterprise. For engineering teams deploying AI in production, DataHub delivers unified context infrastructure across all AI & data assets with enterprise-grade performance.