Senior Platform Engineer
About the Role
We're looking for an exceptional Python engineer to lead development of DataHub's ingestion framework – the core that connects diverse data systems and powers our metadata collection capabilities.
- Scalable, fault-tolerant ingestion systems for enterprise-scale metadata
- Clean, intuitive APIs for our connector ecosystem
- Event-driven architectures for real-time metadata processing
- Schema mapping between diverse systems and DataHub's unified model
- Versioning systems for AI assets (training data, model weights, embeddings)
Requirements
- 4+ years 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
Nice to Have
- Experience with DataHub or similar metadata/ETL frameworks (Airflow, Airbyte, dbt)
- Open-source contributions
- Early-stage startup experience
About DataHub
DataHub is an AI & Data Context Platform adopted by over 3,000 enterprises, including Apple, CVS Health, Netflix, and Visa. Innovated jointly with a thriving open-source community of 13,000+ members, DataHub's metadata graph provides in-depth context of AI and data assets with best-in-class scalability and extensibility. The company's enterprise SaaS offering, DataHub Cloud, delivers a fully managed solution with AI-powered discovery, observability, and governance capabilities.
Organizations rely on DataHub solutions to accelerate time-to-value from their data investments, ensure AI system reliability, and implement unified governance, enabling AI & data to work together and bring order to data chaos.
The Challenge
As AI and data products become business-critical, enterprises face a metadata crisis:
- No unified way to track the complex data supply chain feeding AI systems
- Engineering teams struggling with data discovery, lineage, and governance
- Organizations needing machine-scale metadata management, not just human-browsable catalogs
This is where infrastructure meets impact. The metadata layer you'll build will directly power the next generation of AI systems at massive scale. Your code will determine how safely and effectively thousands of organizations deploy AI, affecting millions of users worldwide.
Benefits
- Competitive Compensation: We offer salaries that reflect your skills, experience, and the impact you make.
- Equity for everyone: Every team member receives an ownership stake in the company.
- Remote Work: All roles are remote unless otherwise specified. Location flexibility with a monthly coworking stipend.
- Comprehensive health coverage: We cover 99% of medical, dental, and vision premiums for employees, and 65% for dependents.
- Flexible savings accounts: FSAs to help cover planned or unexpected healthcare costs, including Dependent Care FSA.
- Support for every path to parenthood: Through Carrot Fertility, we provide inclusive fertility benefits and family-forming support for all U.S. employees.
- Time off that works for you: Unlimited PTO and sick leave policy designed for flexibility, rest, and real life.
Pay
Salary Range: $225,000 to $300,000
Schedule
Bay Area (hybrid, 3 days in Palo Alto office)
Why Join Us
DataHub is at a rare inflection point: we’ve achieved product-market fit, earned the trust of leading enterprises, and secured backing from top-tier investors like Bessemer Venture Partners and 8VC. The context platform market is expected to grow from $1B to $9B in the next five years—and we’re leading the way. By joining our team, you’ll:
- Tackle high-impact challenges at the heart of enterprise AI infrastructure
- Ship production systems that power real-world use cases at global scale
- Collaborate with a high-caliber team of builders who’ve scaled some of the most influential data tools in the world
- Build the next generation of AI-native data systems, including conversational agents, intelligent classification, automated governance, and more