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This is a senior, hands-on Solution Architect position embedded within a data infrastructure and analytics consulting practice. You'll serve as a primary technical authority on Databricks implementations, guiding enterprise clients through complex data platform build-outs and ensuring delivery meets production-grade standards.
Lead and deliver end-to-end Databricks implementation projects at enterprise scale.
Design and architect Lakehouse Platform solutions aligned with client business needs and best practices.
Apply deep Apache Spark expertise to optimize distributed workloads, including Spark runtime tuning and scalability improvements.
Advise on cloud platform architecture across AWS, Azure, and/or GCP environments.
Establish and support CI/CD pipelines for reliable, repeatable production deployments.
Incorporate MLOps practices into platform design and delivery.
Provide technical consulting and advisory support throughout the engagement lifecycle.
10+ years of consulting experience, with at least 7 years focused on Data Engineering, Data Platforms, and Analytics.
Proven hands-on delivery of 6–8+ Databricks implementation projects.
Strong understanding of the Databricks Lakehouse Platform, including current capabilities and best practices.
Deep expertise in Apache Spark and distributed computing, including Spark runtime internals.
Databricks Data Engineering Professional Certification (strongly preferred).
Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP); multi-cloud experience is a plus.
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.
Must be authorized to work in the United States; visa sponsorship is not available for this role.
Up to $80/hr on W2. Visa sponsorship is not available.
Fully remote (North America).
