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Home  | Clera  | Resident Solution Architect (D...
  • About the Role

    We are a privately held IT and MarTech consultancy working with enterprise clients across regulated industries. We are looking for a senior, hands-on Resident Solution Architect with deep expertise in the Databricks Lakehouse Platform to join our team on a W2 contract basis. In this role, you will lead and deliver large-scale Databricks implementations, advise clients on platform best practices, and serve as a trusted technical authority across data engineering and analytics engagements.

    What You'll Do

    • Architect, design, and deliver end-to-end Databricks implementations for enterprise clients.

    • Serve as a hands-on solution architect, guiding technical teams through complex data platform builds.

    • Apply deep knowledge of the Databricks Lakehouse Platform — including current capabilities, Delta Lake, and best practices — to drive client outcomes.

    • Leverage Apache Spark expertise (including runtime internals) for performance tuning, optimization, and scalability of large-scale data platforms.

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

    • Advise on and implement MLOps workflows in collaboration with data science teams.

    • Work across one or more major cloud platforms (AWS, Azure, GCP) to deliver scalable, cloud-native solutions.

    • Translate complex technical requirements into actionable architectural recommendations for both technical and non-technical stakeholders.

    What We're Looking For

    Required:

    • Must be authorized to work in the United States without visa sponsorship (W2 contract — no C2C or 1099).

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

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

    • Strong understanding of the Databricks Lakehouse Platform, including platform capabilities and best practices.

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

    • Completed Databricks Data Engineering Professional Certification.

    • Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.

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

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

    • Working knowledge of MLOps principles and tooling.

    Nice to Have:

    • Multi-cloud experience spanning two or more of AWS, Azure, and GCP.

    Compensation & Benefits

    • Pay Rate: Up to $80/hr on W2

    • W2 contract engagement

    Location

    • Based in San Ramon, CA

    • Visa sponsorship is not available for this role — candidates must be authorized to work in the US without sponsorship.

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