Lead Data Engineer

gxl • United State
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AI Summary

Lead Data Engineer to own data infrastructure for GXL's AI products like Paperclip. Design and maintain scalable ETL/ELT pipelines across structured and unstructured data sources. Requires 2+ years of data engineering experience with cloud data warehouses and performance optimization.

Key Highlights
Own data infrastructure powering AI-native scientific discovery tools
Design and maintain scalable ETL/ELT pipelines across structured and unstructured data
Lead architectural decisions on new data systems
Key Responsibilities
Design and maintain scalable ETL/ELT pipelines across structured and unstructured data sources
Own database performance: schema design, indexing strategies, query optimization, and capacity planning
Build and improve data warehousing infrastructure
Establish and enforce data quality standards, validation frameworks, and monitoring
Partner closely with research and product teams to understand data requirements and ship reliably
Lead architectural decisions on new data systems
Technical Skills Required
ETL/ELT pipelines database performance schema design indexing strategies query optimization capacity planning data warehousing infrastructure data quality standards validation frameworks monitoring cloud data warehouse
Benefits & Perks
200k+ annual compensation
equity
visa sponsorship
Nice to Have
Experience in AI/ML infrastructure or working alongside model training pipelines
Familiarity with vector databases or embedding pipelines
Experience with streaming data
General understanding of biotechnology industry

Job Description


About GXL

Generative Expert Labs (GXL) is building the next generation of AI-native tools for scientific discovery. We're a fast-moving team that ships products that agents and humans love, and we're looking for engineers who want to disrupt the existing agentic ecosystem.


The Role

We're looking for a Lead Data Engineer to own the data infrastructure that powers GXL's AI products (eg. Paperclip). You'll be responsible for designing, building, and maintaining the pipelines, warehouses, and systems that our research and products depend on.


What You'll Do

- Design and maintain scalable ETL/ELT pipelines across structured and unstructured data sources

- Own database performance: schema design, indexing strategies, query optimization, and capacity planning

- Build and improve data warehousing infrastructure

- Establish and enforce data quality standards, validation frameworks, and monitoring

- Partner closely with research and product teams to understand data requirements and ship reliably

- Lead architectural decisions on new data systems


What We're Looking For

- 2+ years of data engineering experience, with a track record of owning complex pipelines end-to-end

- Deep experience with ETL/ELT design patterns and tools

- Experience with at least one major cloud data warehouse

- Solid understanding of data modeling, normalization, and warehousing best practices

- Experience diagnosing and resolving performance bottlenecks at scale

- Comfort operating in ambiguous, fast-moving environments


Nice to Have

- Experience in AI/ML infrastructure or working alongside model training pipelines

- Familiarity with vector databases or embedding pipelines

- Experience with streaming data

- General understanding of biotechnology industry


Compensation

200k+, Offers Equity


Visa sponsorship

We do sponsor visas. While we can’t guarantee sponsorship for every candidate or role, if we make you an offer, we’ll make every reasonable effort to support your visa process. We partner with experienced immigration counsel to help facilitate sponsorship where possible.



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