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Databricks Architect

TekLeaders, IncSan Francisco, CA🇺🇸United StatesPosted Sep 30, 2026

Why This Role Stands Out

Elevate your career as a Databricks Architect with TekLeaders, Inc., where you'll drive innovative data solutions and gain invaluable experience in a hybrid, PST-focused environment. This role is perfect for seasoned data professionals with 10+ years of consulting experience who thrive on designing and implementing modern data platforms. Seize this opportunity to make a significant impact and advance your expertise.

Quick Overview

Seniority

Mid Senior

Work mode

Hybrid

Location

San Francisco, CA, United States

Posted

2 weeks ago

AWSETLMLOpsMLflowMachine LearningApacheApache SparkAzureDatabricksGitHub ActionsGitLab CIGoogle CloudJenkinsUnity

Job Description

DataBricks Architect (Resident Solution Architect )

Location: San Francisco, CA (Remote is ok if not able to find local.. need to work in PST Time Zone)

Duration: 8-12 months

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