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Databricks Architect

Source Code Technologies LLCSan Francisco, CA🇺🇸United StatesPosted 24 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
San Francisco, CA, United States
Posted
3 days ago
AWSETLMLOpsMLflowMachine LearningApacheApache SparkAzureDatabricksGitHub ActionsGitLab CIGoogle CloudJenkinsUnity

Job Description

Title :: Databricks Architect (Resident Solution Architect - Banking experience is needed)

Experience : 15+ years experience required

 

Job description:

Core skills needed –

  • 12-15+ years of experience in Data Engineering, Data Platforms,  Data Analytics, and Modern Data Warehouse solutions, with 10+ years of overall consulting and client-facing delivery experience.
  • Demonstrated success delivering 6-8+ end-to-end Databricks implementations, serving as a hands-on developer, technical lead, or solution architect.
  • Databricks Data Engineering Professional certification (or equivalent advanced Databricks certification) with completion of all recommended learning paths and coursework.
  • Databricks has a Databricks Solutions Architect Champion program- this will be good to have
  • Strong expertise in designing and implementing cloud-native data platforms across AWS, Azure, and/or Google Cloud Platform, with deep hands-on proficiency in at least one cloud ecosystem.
  • Advanced knowledge of Apache Spark, including performance optimization, partitioning strategies, execution plans, memory management, and Spark runtime internals.
  • Extensive hands-on experience developing scalable ETL/ELT pipelines using Databricks, Delta Lake, Structured Streaming, and modern data engineering frameworks.
  • Experience implementing DevOps and CI/CD practices for production-grade data solutions using tools such as Azure DevOps, GitHub Actions, GitLab CI/CD, or Jenkins.
  • Working knowledge of MLOps principles, machine learning lifecycle management, model deployment, and monitoring within enterprise environments.
  • Current and broad understanding of the Databricks Lakehouse Platform, including Delta Lake, Unity Catalog, Workflows, MLflow, Delta Live Tables, and other platform capabilities.
  • Strong experience tuning large-scale distributed workloads and designing highly performant, scalable, and cost-efficient data processing solutions.
  • Ability to troubleshoot complex data platform challenges and recommend architecture patterns aligned with business and technical requirements

 

 

 

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