Senior Databricks Solution Architect – Lakehouse & Data Engineering | Contract | Remote (PST)
Contract Independent
Contract W2
12 Months
No Travel Required
Remote
Depends on Experience
Anagha Techno Soft
Fitment
Dice Job Match Score™
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Job Details
Skills
- Databricks Solution Architecture
- Databricks Implementation Delivery
- Apache Spark / PySpark
- Delta Lake / Lakehouse
- Cloud Architecture
- ETL/ELT & Structured Streaming
- Unity Catalog & Governance
- DevOps / CI/CD
- MLOps / MLflow
- Client Consulting & Technical Leadership
Summary
Senior Databricks Solution Architect – Lakehouse & Data Engineering | Contract | Remote (PST)
Senior Databricks Solution Architect – Lakehouse & Data Engineering
Location: San Francisco, CA (Remote Considered)
Job Type: Contract
Experience: 12–15+ Years
Time Zone: Pacific Time
Job Type: Contract
Experience: 12–15+ Years
Time Zone: Pacific Time
Ideal Candidate Profile
A hands-on architect who can confidently lead client conversations, make sound architecture decisions, build and optimize production solutions, and guide engineering teams through complex Databricks implementations.
Job Summary
We are seeking an experienced Senior Databricks Solution Architect with a strong combination of enterprise solution architecture, hands-on data engineering, and client-facing consulting experience.
The ideal candidate will have successfully designed, implemented, and optimized multiple enterprise-scale Databricks solutions, with deep expertise in Apache Spark, Delta Lake, Lakehouse architecture, and cloud-native data platforms. This role requires someone who can lead architecture discussions while remaining actively involved in technical design, development, performance tuning, and troubleshooting.
Key Responsibilities
- Design and implement scalable, secure, and cost-efficient enterprise data platforms using the Databricks Lakehouse Platform.
- Lead end-to-end Databricks implementations, from architecture and solution design through development, deployment, and production optimization.
- Develop and optimize scalable ETL/ELT pipelines using PySpark, Apache Spark, Delta Lake, and Structured Streaming.
- Design cloud-native data solutions across AWS, Microsoft Azure, and/or Google Cloud Platform.
- Optimize distributed data processing through partitioning strategies, execution-plan analysis, memory management, and performance tuning.
- Implement platform capabilities including Unity Catalog, Databricks Workflows, Delta Live Tables/Lakeflow, and MLflow.
- Establish DevOps and CI/CD practices using Azure DevOps, GitHub Actions, GitLab CI/CD, Jenkins, or similar tools.
- Apply data governance, security, monitoring, reliability, and cost-optimization best practices.
- Provide hands-on technical leadership, troubleshoot complex platform challenges, and recommend appropriate architecture patterns.
- Lead client workshops, communicate architectural decisions, and translate business requirements into technical solutions.
Required Qualifications
- 12–15+ years of experience in data engineering, data platforms, data analytics, or modern data warehouse solutions.
- 10+ years of consulting, client-facing delivery, or enterprise technology implementation experience.
- Demonstrated success delivering multiple end-to-end Databricks implementations, ideally 6–8 or more.
- Strong hands-on proficiency in at least one major cloud platform: AWS, Azure, or Google Cloud Platform.
- Advanced knowledge of Apache Spark, PySpark, Spark SQL, distributed computing, and performance optimization.
- Extensive experience with Databricks, Delta Lake, scalable ETL/ELT pipelines, and modern data engineering frameworks.
- Strong understanding of Lakehouse architecture, Unity Catalog, workflow orchestration, and production-grade data platform design.
- Experience with CI/CD, DevOps, production monitoring, and deployment automation.
- Working knowledge of MLOps, MLflow, machine learning lifecycle management, and model monitoring.
- Excellent analytical, troubleshooting, communication, and technical leadership skills.
Preferred Qualifications
- Databricks Certified Data Engineer Professional certification or an equivalent advanced Databricks credential.
- Databricks Solutions Architect Champion recognition.
- Experience in public sector, banking/financial services, or healthcare environments.
- Experience with large-scale platform modernization, data governance, and enterprise cloud migrations.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 91163035
- Position Id: 9129502
- Posted 1 hour ago
Company Info
About Anagha Techno Soft
Anagha Techno soft is a reputable company specializing in IT services and staff augmentation. With a commitment to delivering cutting-edge solutions and top-notch services, Anagha Techno soft caters to a diverse clientele ranging from small businesses to large enterprises.
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