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Remote Databricks Architect Jobs in Arizona (NOW HIRING)

Koantek

Databricks Platform Architect

Chandler, AZ · Remote

Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead ... Validate, refine, and own the target architecture on Databricks. Define robust migration strategies ...

Deloitte

Databricks Manager

Tempe, AZ · On-site +1

Lead solution reviews and design update discussions to drive architecture decisions and secure ... remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a ...

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Remote Databricks Architect information

Can you work remotely as an architect?

Remote work is possible for a Databricks Architect, especially with the increasing adoption of flexible work arrangements in the tech industry. Many organizations allow architects to perform their duties remotely, utilizing cloud platforms, collaboration tools, and virtual communication. However, some roles may require on-site presence for meetings, training, or specific project needs.

Does Databricks allow remote work?

Remote Databricks Architects can often work remotely, depending on the company's policies and project requirements. Many organizations in data engineering and analytics support remote work, especially for roles involving cloud platforms and tools like Databricks, which facilitate collaboration and remote access. Candidates should verify specific employer policies and ensure they have the necessary technical setup for remote work environments.

What is the difference between Remote Databricks Architect vs Remote Data Engineer?

AspectRemote Databricks ArchitectRemote Data Engineer
Primary FocusDesigning and implementing data solutions on Databricks platformBuilding and maintaining data pipelines and infrastructure
Required SkillsDatabricks, Spark, cloud platforms, architecture designETL, SQL, Python, cloud data tools
CertificationsDatabricks certifications, cloud certificationsCloud certifications, SQL, Python skills
Work EnvironmentCollaborates with data teams, architects, and stakeholdersWorks on data pipeline development, data modeling

While both roles work within data environments and often in cloud settings, the Remote Databricks Architect focuses on designing scalable data solutions using Databricks, whereas the Remote Data Engineer primarily builds and maintains data pipelines and infrastructure. The architect role emphasizes architecture and strategy, while the data engineer role emphasizes implementation and operational tasks.

Will AI replace Solution Architect?

AI is unlikely to fully replace Solution Architects, as their role involves complex problem-solving, designing scalable systems, and understanding business needs that require human judgment. Instead, AI tools can augment their work by automating routine tasks and providing data-driven insights, allowing Solution Architects to focus on strategic planning and innovative solutions. Success in this role often depends on technical expertise, communication skills, and experience with cloud platforms like Databricks.

How much do Databricks architects make?

Databricks architects typically earn between $120,000 and $180,000 annually, depending on experience, location, and certifications. Senior roles or those with specialized skills in cloud platforms and big data tools may command higher salaries.
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Remote Databricks Architect jobs near you
Databricks Platform Architect

Databricks Platform Architect

Koantek

Chandler, AZ • Remote

Contractor

Posted 8 days ago

Job description

Job Title: Lead Data Platform Architect / Data bricks Migration Lead Location: Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead Data Platform Architect / Migration Specialist to spearhead the modernization of our core enterprise financial and tax allocation engines. In this role, you will lead the architectural design, definition of migration strategies, and hands-on implementation to transition large-scale legacy relational database systems (SQL Server/T-SQL) into a modern, cloud-native Databricks Lakehouse platform. The ideal candidate will have extensive experience in high-throughput distributed systems, Databricks compute optimization, performance tuning, and complex pipeline orchestration.

Key Responsibilities Architecture & Strategy: Validate, refine, and own the target architecture on Databricks. Define robust migration strategies and production-ready reference patterns to convert 150+ complex stored procedures into PySpark and Structured/Declarative Pipelines (SDP). Pipeline Engineering: Design distributed processing frameworks, control flows, and configuration-driven parameter handling for both full and incremental recalculation modes.

Performance Optimization: Address performance deltas between small and large workloads. Architect and implement acceleration techniques such as caching, partition pruning, cluster sizing, and offline/pre-calculation strategies to maintain sub-30-second user-facing reporting SLAs. Orchestration & Observability: Design and deploy enterprise-level pipeline orchestration using tools like Apache Airflow or Databricks Workflows.

Integrate robust logging, error handling, and observability patterns into existing enterprise monitoring frameworks. Governance & Security: Implement data governance models, data lineage, and schema evolution utilizing tools like Unity Catalog. AI-Assisted Delivery & Code Quality: Establish best practices for AI-assisted code generation (e.g., using Claude or advanced LLMs), providing code-review patterns and refactoring frameworks to ensure maintainable and performant output

Team Enablement: Lead code walkthroughs, design reviews, and pair-programming sessions with the development team to accelerate knowledge transfer and technical excellence. Required Technical Skills & Qualifications Core Big Data Platform: Deep expert-level knowledge of Databricks (Lakehouse architecture, Delta Lake, Unity Catalog) and Apache Spark / PySpark. Legacy Database Expertise: Strong background in relational databases, with advanced proficiency in SQL Server, T-SQL, and Stored Procedures.

Ability to reverse-engineer and refactor legacy database logic into distributed paradigms. Orchestration Tools: Hands-on experience with Apache Airflow or similar modern workflow orchestrators. Performance Tuning: Proven track record in cost optimization (FinOps), cluster tuning, autoscaling configurations, and handling skewed data profiles.

CI/CD & DevOps: Experience with Infrastructure as Code (Terraform), data build tool (dbt), testing frameworks (PyTest), and automated Git-based workflows. Experience Level: 10+ years of experience in Data Engineering/Architecture, with at least 3+ years specifically leading large-scale cloud data migrations. Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

Preferred Certifications Databricks Certified Data Engineer Associate / Professional Databricks Certified Solutions Architect AWS Certified Database Specialist or equivalent Cloud Certifications

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