Resident Solution Architect Databricks - Clera San Francisco
Overview
We seek a senior Resident Solution Architect specializing in the Databricks Lakehouse Platform to lead large-scale implementations for enterprise clients. This W2 contract role involves designing end-to-end Databricks solutions scaling across AWS Azure GCP while advising on platform best practices and MLOps workflows.
What You'll Do7
- 1Architect and deliver end-to-end Databricks implementations for enterprise clients
- 2Guide technical teams through complex data platform builds using deep Lakehouse expertise
- 3Apply knowledge of Delta Lake and Spark runtime internals for performance tuning and scalability
- 4Design and support CI/CD pipelines for production data platform deployments
- 5Advise on MLOps workflows in collaboration with data science teams
- 6Work across multiple cloud platforms to deliver scalable cloud-native solutions
- 7Translate complex technical requirements into actionable recommendations for stakeholders
Requirements10
- 1Authorized to work in the United States without visa sponsorship
- 210+ years of consulting experience with 7+ years focused on Data Engineering and Analytics
- 3Hands-on delivery of 6–8+ Databricks implementation projects at enterprise scale
- 4Strong understanding of Databricks Lakehouse Platform capabilities and best practices
- 5Deep expertise in Apache Spark and distributed computing including runtime internals
- 6Completed Databricks Data Engineering Professional Certification
- 7Hands-on experience with AWS Azure or GCP
- 8Proven experience with performance tuning optimization and scalability of large-scale platforms
- 9Solid understanding of CI/CD pipelines for production deployments
- 10Working knowledge of MLOps principles and tooling
Salary Insight
$80k per year
Location
Required Skills
Similar open positions
Explore active roles that match your skills and interests.
SVCS Huron Consulting Services LLC
VerifiedDatabricks Technical Architect
Lead Databricks technical architecture and productionize Lakehouse platforms for clients. Translate business requirements into technical designs, build and scale Delta Lake pipelines, and integrate GenAI solutions. Partner with functional leads to ensure platform decisions support data quality and governance.
Trebecon LLC
VerifiedAzure Databricks Architect
Lead design of scalable enterprise data platforms using Azure Databricks and Lakehouse architecture. Own end-to-end data engineering initiatives to drive high-performance ETL/ELT pipelines. Implement solutions leveraging PySpark Spark SQL and Databricks Workflows. Differentiate by scaling data infrastructure for Tampa based teams.

TECHNEPTUNE CONSULTING INC
VerifiedData Solution Architect - Expertise in AWS and Data Platforms
Lead ownership of scalable data solutions at Technep Tuning Inc. in San Francisco. Design and deliver enterprise-grade data platforms leveraging advanced cloud technologies. This role focuses on architecting robust data ecosystems that drive business insights and operational efficiency.

MOONITSolutions Inc.
VerifiedSenior Data Engineer (Databricks)
Lead architectural ownership and end-to-end system design for production Databricks solutions. Scale high-performance data platforms to support enterprise-wide analytics. Differentiate by mastering Delta Lake and Unity Catalog while driving performance improvements.

Anblicks
VerifiedLead Databricks Engineer, Lakehouse & ETL Pipelines
You will own the Lakehouse platform architecture for Anblicks in Dallas, designing and implementing end-to-end data solutions on Databricks. You will define best practices and build scalable ETL/ELT pipelines that power Spark workloads. Working closely with stakeholders, you will shape technical strategy and deliver production-grade data systems. This role centers on driving performance, cost, and scalability across a growing data estate.
brillio-2
VerifiedDatabricks Architect R01568474
Lead the design and implementation of modern data and AI platforms. The ideal candidate brings deep expertise in the Databricks ecosystem or Google Cloud Platform (GCP) combined with strong data engineering and architecture fundamentals. This role defines scalable data architectures enables AI adoption and drives modernization across data analytics and AI capabilities.