About The Role

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.