Staff Backend Engineer (Catalog)
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Salary
$225k – $300k per year
Location
Hybrid (Palo Alto, United States)
Seniority
Staff · 8+ years exp
Employment
Full-Time
Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Jul 13, 2026.
Overview
Company
Impact
Profile match
DataHub, formerly Acryl Data, runs the managed service behind the open-source metadata platform of the same name that was first developed inside LinkedIn and is now used by thousands of engineering organisations. Its product gives data teams a searchable catalog with column-level lineage, ownership records, quality monitoring and access policies across warehouses, streaming systems and business intelligence tools. Customers use it to answer who owns a dataset, what will break when it changes and which reports depend on it before a migration begins.
Backed by Bessemer Venture Partners, 8VC, Abstract
Join our team as a Staff Backend Engineer (Catalog) and play a crucial role in addressing the metadata crisis faced by enterprises as AI and data products become business-critical. You will lead the development of DataHub's Platform framework, which connects diverse data systems and powers our metadata collection capabilities. Your work will directly impact the deployment of AI systems at massive scale, affecting millions of users worldwide.
Missions
- Lead the development of DataHub's Platform framework, focusing on connecting diverse data systems and enhancing metadata collection capabilities.
- Design and implement scalable, fault-tolerant ingestion systems for enterprise-scale metadata, ensuring clean and intuitive APIs for the connector ecosystem.
- Collaborate with engineering teams to address data discovery, lineage, and governance challenges, and contribute to the overall architecture of the metadata layer.
Profil recherché
- 8+ years building production-grade distributed systems- Built and maintained online applications serving live traffic at scale (100+ QPS)
- Designed indexing, storage, and data architectures to make large-scale data accessible to online services
- Advanced Python and API design expertise
- Experience with high-scale data processing or integration frameworks
- Designed and scaled distributed systems
- Strong systems knowledge and distributed architecture experience
- Hands-on experience developing in a tight loop with LLMs and applying best practices for scalable LLM development
- Set up monitoring and alerting for services
- Proven track record solving complex technical challenges
- One of Java/Scala/Kotlin/C#/Go - very strong nice-to-have / borderline must-have
- Python/TypeScript/Node.js - nice-to-have
- CI/CD deployment pipelines
- AWS
- Kubernetes/Docker
- Microservice Architecture
- Early-stage startup experience
- Experience fine-tuning LLM-powered applications exposed to end users
- Experience building and maintaining services that make calls to LLMs in order to serve live traffic
- Open-source contributions
- Experience with DataHub or similar metadata/ETL frameworks (Airflow, Airbyte, dbt)
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