Resident Solution Architect (Databricks)
Role Overview
Senior, hands-on architecture role delivering large-scale Databricks implementations for enterprise clients.
Combines data engineering, cloud architecture, client advisory, and technical delivery across production-grade environments.
Work includes distributed computing, performance optimization, CI/CD, and MLOps challenges at significant scale.
Key Skills for This Role
Full Job Posting
Role overview
Senior, hands-on architecture role delivering large-scale Databricks implementations for enterprise clients.
Combines data engineering, cloud architecture, client advisory, and technical delivery across production-grade environments.
Work includes distributed computing, performance optimization, CI/CD, and MLOps challenges at significant scale.
Accountabilities
- Lead end-to-end Databricks implementation initiatives from architecture and design through deployment and production.
- Advise enterprise clients on Lakehouse architecture, platform capabilities, best practices, roadmaps, and implementation strategies.
- Design scalable and resilient data platforms for complex enterprise workloads and evolving business requirements.
- Optimize distributed data systems and resolve performance and scalability issues across production environments.
- Serve as a hands-on technical lead for cloud implementations across AWS, Azure, and/or GCP.
- Design, implement, and support CI/CD pipelines for reliable production data-platform deployments.
- Apply MLOps principles across data engineering and machine learning development and deployment workflows.
- Collaborate with client technical teams and stakeholders to guide adoption of modern Lakehouse practices.
Requirements
- 10+ years of consulting experience, including at least 7 years in data engineering, data platforms, analytics, or related disciplines.
- Hands-on delivery of approximately 6–8 or more enterprise-scale Databricks implementation projects.
- Deep Apache Spark and distributed computing expertise, including Spark runtime internals.
- Extensive knowledge of the Databricks Lakehouse Platform, capabilities, architectural patterns, and best practices.
- Experience optimizing large-scale data platforms for performance, reliability, and scalability.
- Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.
- Strong consulting, communication, and client-facing skills for influencing architectural decisions.
- Databricks Data Engineering Professional Certification is strongly preferred.
Compensation
- Compensation is up to $80 per hour on W2.
Workplace
- The position is fully remote with flexibility to work from anywhere in North America.
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