Data Engineer

San Francisco, California, United StatesHybridFull Time$180,000–$220,000 /yrPosted 2 months agoVisa sponsorship available

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Role summary

A fast-growing SaaS startup in the cloud financial management sector seeks a Data Engineer to manage and scale its data infrastructure. This role involves working with massive semi-structured data, building reliable pipelines, and ensuring end-to-end data quality. The engineer will design storage systems (ClickHouse, Parquet, S3), develop ETL processes for millions of rows of cloud billing data, implement validation systems in Python and SQL, and model complex schemas. The position requires 3+ years of experience with data products, strong Python and SQL skills, and comfort with columnar databases and cloud storage. Experience with ClickHouse, Airflow, or cloud billing data is a plus. This is a hybrid role based in the San Francisco Financial District.

🚀 About the Role

A fast-growing SaaS startup in the cloud financial management space is hiring a Data Engineer to own and scale the data infrastructure powering a platform built for large enterprises with complex cloud spending needs. This is a technically rich role for an engineer who loves wrangling massive volumes of semi-structured data, building bulletproof pipelines, and caring deeply about data quality end to end.

You'll work across the full data stack, from pipeline architecture to schema design to quality control, in an environment where your work directly drives high-stakes financial decisions for enterprise customers.

*Candidates must currently be located in the San Francisco Bay Area. This role is hybrid (3 days in-office, 2 days remote) in the SF Financial District.*

🛠 What You'll Do

Design efficient data storage and retrieval systems using ClickHouse, Parquet, and S3
Build and maintain ETL pipelines processing hundreds of millions of rows of cloud billing data
Develop robust data validation and quality control systems in Python and SQL
Design and evolve data models for complex, constantly changing cloud billing schemas
Build and optimize Airflow workflows for reliable, scalable data processing
Collaborate with the engineering team to investigate and resolve data quality issues
Scale data infrastructure as the platform expands to new cloud providers and use cases

✅ What We're Looking For

3+ years of experience with data products: warehouses, lakehouses, OLAPs, ETL pipelines, or job queues
Intermediate to strong Python skills with a software engineering foundation
Strong SQL chops including CTEs, window functions, and query optimization
Experience building data validation and quality control systems
Comfort with columnar databases, Parquet, and cloud storage (S3)
Startup experience and the ability to move fast in ambiguous, evolving environments
A genuine fastidiousness about data quality, even when there's no answer key

⭐ Bonus Points For

Hands-on experience with ClickHouse or other OLAP datastores
Familiarity with cloud billing data or cost management tooling (AWS CUR, etc.)
Experience with Airflow or similar workflow orchestration tools
Backend engineering experience beyond data pipelines

💥 Why Apply?

End-to-end ownership of data products that directly impact enterprise customer outcomes
Genuinely complex technical challenges at scale in a specialized, fast-growing domain
Small, senior team where your contributions are visible and matter immediately
Ground-floor opportunity at a well-backed startup with real revenue and strong domain expertise

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