Resident Solution Architect (Databricks)
Clera · remote · posted Sep 16, 2026
Open to candidates in Canada, Mexico and United States
What this role actually asks for
Extracted by RemoteHuntMust have
- •10+ years consulting experience
- •7+ years Data Engineering/Platforms/Analytics
- •6-8+ Databricks implementation projects
- •Databricks Architect background
- •Apache Spark & distributed computing expertise
- •Cloud platform experience (AWS, Azure, GCP)
Nice to have
- •Multi-cloud experience
- •Databricks Data Engineering Certification
Tools and technologies
Worth checking before you apply
- ⚠US-W2 only
- ⚠no visa sponsorship
The full posting
About the Role This is a senior, hands-on Solution Architect role focused on Databricks, sitting within a data infrastructure and analytics practice that serves complex enterprise clients. You will own end-to-end Databricks implementations and translate deep platform expertise into scalable, production-ready data lakehouse solutions that directly drive client outcomes.
What You'll Do Lead and deliver Databricks implementation projects at enterprise scale, from architecture design through production deployment. Apply strong hands-on expertise in Apache Spark and distributed computing, including Spark runtime internals, to solve complex data engineering challenges.
Design and optimize large-scale data platforms for performance, scalability, and reliability across major cloud environments. Establish and apply CI/CD pipeline best practices for production data platform deployments. Integrate MLOps patterns into data platform solutions where appropriate.
Advise clients on Databricks Lakehouse Platform capabilities, best practices, and roadmap alignment. What We're Looking For 10+ years of consulting experience, including 7+ years focused on Data Engineering, Data Platforms, and Analytics. Hands-on delivery of 6 to 8 or more Databricks implementation projects in a Solution Architect capacity.
Established Databricks Architect or Databricks Solution Architect background, not adjacent data engineering experience alone. Strong expertise in Apache Spark and distributed computing, including internals. Databricks Data Engineering Professional Certification (required or strongly preferred).
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 deployments. Working knowledge of MLOps practices.
Experience with performance tuning, optimization, and scalability of large-scale data platforms. Must be authorized to work in the United States without visa sponsorship (W2 contract). 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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