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Salary
up to $160k per year
Location
In office
Seniority
Architect · 10+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Clera is a San Francisco-based AI recruiting and talent-matching platform designed as an AI talent agent for candidates and hiring teams. Acting as a tech-driven alternative to traditional headhunting, Clera directly connects job seekers to open roles at top startups backed by venture firms like Andreessen Horowitz (a16z), Y Combinator, Index Ventures, and General Catalyst.

About the Role

This is a senior, hands-on Solution Architect role focused on delivering large-scale Databricks implementations for enterprise clients. You'll sit at the intersection of data engineering and client advisory, helping organizations architect and optimize modern Lakehouse platforms. The work has real impact - shaping production-grade data infrastructure across complex, regulated environments.

What You'll Do

  • Lead end-to-end Databricks implementation projects, from architecture design through production deployment.

  • Advise enterprise clients on Lakehouse platform best practices, capabilities, and roadmap decisions.

  • Tune and optimize large-scale distributed data systems for performance and scalability.

  • Design and support CI/CD pipelines for data platform production deployments.

  • Apply MLOps patterns to bridge data engineering and machine learning workflows.

  • Serve as a hands-on technical lead, working directly in cloud environments (AWS, Azure, and/or GCP).

What We're Looking For

  • 10+ years of consulting experience, with at least 7 years focused on Data Engineering, Data Platforms, and Analytics.

  • Hands-on delivery of 6-8+ Databricks implementation projects at enterprise scale.

  • Strong expertise in Apache Spark and distributed computing, including Spark runtime internals.

  • Deep understanding of the Databricks Lakehouse Platform, including current capabilities and best practices.

  • Databricks Data Engineering Professional Certification (strongly preferred).

  • Proven experience with performance tuning, optimization, and scalability of large-scale data platforms.

  • Hands-on experience with at least one major cloud platform - AWS, Azure, or GCP; multi-cloud experience is a plus.

  • Solid understanding of CI/CD pipelines for production data deployments.

  • Working knowledge of MLOps concepts and practices.

  • Must be authorized to work in the United States; visa sponsorship is not available for this role.

Compensation & Benefits

Up to $80/hr on W2. No visa sponsorship available.

Location

Fully remote - open to candidates based anywhere in North America.

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