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Databricks Architect Jobs in Washington (NOW HIRING)

eSolutionsFirst, LLC

Databricks Architect

Mclean, VA · On-site

$66.50 - $87.25/hr

About the Role We are seeking an experienced Databricks Resident Solutions Architect (RSA) to lead the architecture, implementation, and optimization of enterprise Databricks Lakehouse solutions.

PamTen Inc

Databricks Architect

Washington, DC · On-site

$73 - $96/hr

PamTen Inc is seeking a Databricks Architect to design and implement enterprise-scale solutions on the Databricks Lakehouse Platform. The role involves architecting data pipelines, developing data ...

eSolutionsFirst, LLC

Databricks Architect

Mclean, VA · On-site

$66.50 - $87.25/hr

Databricks Architect 12 Months contract extension/ Fulltime job Vienna, VA About the Role * We are seeking an experienced Databricks Resident Solutions Architect (RSA) to lead the architecture ...

eSolutionsFirst

Data Solutions Architect-Databricks

Vienna, VA · On-site

$64 - $82.25/hr

... Architect to join their Professional Services team. The role involves working with clients to address big data challenges using the Databricks platform, focusing on data engineering, data science ...

ECS

Senior Databricks Platform Engineer

Quantico, VA · On-site

$140K - $165K/yr

In-depth knowledge of Databricks architecture, including workspaces, clusters, storage, notebook development, and automation capabilities. * Deep expertise in Databricks Unity Catalog, workspace ...

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Databricks Architect information

What is a Databricks Architect?

A Databricks Architect is an IT professional who designs, implements, and manages data solutions using the Databricks platform, which is built on Apache Spark. They are responsible for creating scalable data pipelines, optimizing data workflows, and ensuring security and compliance within the cloud environment. Databricks Architects often work closely with data engineers, data scientists, and business stakeholders to deliver robust analytics solutions that drive business insights. Their expertise helps organizations leverage big data technologies efficiently and effectively.

What are the key skills and qualifications needed to thrive as a Databricks Architect?

To thrive as a Databricks Architect, you need strong expertise in big data engineering, cloud platforms (such as Azure or AWS), distributed computing, and proficiency in languages like Python or Scala, typically supported by a relevant degree and cloud certifications. Familiarity with Databricks Workspace, Apache Spark, Delta Lake, and CI/CD tools is crucial for designing and implementing scalable data solutions. Excellent problem-solving, communication, and project management skills set top performers apart by enabling effective collaboration and solution delivery. These competencies are essential for architecting reliable, high-performance data platforms that drive business insights and innovation.

What are some common challenges Databricks Architects face when designing large-scale data solutions?

Databricks Architects often encounter challenges such as optimizing cluster performance for cost and efficiency, ensuring data security and compliance across distributed environments, and integrating Databricks with legacy systems or diverse data sources. They must carefully design data pipelines and workflows to handle large volumes of data without bottlenecks, and also collaborate closely with data engineers, data scientists, and IT teams to align on best practices. Staying updated with evolving Databricks features and cloud platform updates is also essential for success in this dynamic role.

What is the difference between Databricks Architect vs Data Engineer?

AspectDatabricks ArchitectData Engineer
Primary FocusDesigning and implementing data solutions on Databricks platformBuilding, maintaining, and optimizing data pipelines and infrastructure
Skills & CertificationsDatabricks certifications, Spark, cloud platforms (AWS, Azure), SQLSQL, ETL tools, cloud platforms, programming (Python, Scala)
Work EnvironmentData platforms, cloud environments, collaboration with data teamsData pipelines, databases, cloud infrastructure, scripting

While both roles work with data and cloud platforms, a Databricks Architect primarily focuses on designing and implementing data solutions using Databricks, whereas a Data Engineer builds and maintains the data pipelines and infrastructure that support these solutions. The Architect often oversees the technical design, while the Engineer handles the day-to-day pipeline development.

What are the most commonly searched types of Databricks Architect jobs in Washington?

The most popular types of Databricks Architect jobs in Washington are:

What are popular job titles related to Databricks Architect jobs in Washington?

For Databricks Architect jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Databricks Architect jobs in Washington look for?

The top searched job categories for Databricks Architect jobs in Washington are:

What cities in Washington are hiring for Databricks Architect jobs?

Cities in Washington with the most Databricks Architect job openings:

Databricks Architect jobs near you
Infographic showing various Databricks Architect job openings in Washington as of August 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 70% Physical, 7% Hybrid, and 23% Remote job distribution.

Databricks Architect

eSolutionsFirst, LLC

Mclean, VA • On-site

$66.50 - $87.25/hr

Other

Re-posted 23 hours ago

Job description

About the Role

We are seeking an experienced Databricks Resident Solutions Architect (RSA) to lead the architecture, implementation, and optimization of enterprise Databricks Lakehouse solutions. This is a hands-on, customer-facing role requiring deep Databricks expertise, strong architecture skills, and the ability to guide engineering and data teams.

Key Responsibilities

  • Lead the architecture and delivery of enterprise Databricks Lakehouse implementations.
  • Design scalable solutions using Databricks, Delta Lake, Apache Spark, Unity Catalog, and Databricks Workflows.
  • Provide hands-on technical leadership for complex Databricks data engineering projects.
  • Optimize Spark and Databricks workloads for performance, scalability, reliability, and cost.
  • Design and implement enterprise ETL/ELT pipelines using Databricks, Spark, Python, and SQL.
  • Establish Unity Catalog governance, security, access controls, and data management practices.
  • Support migration and modernization of legacy data platforms to Databricks Lakehouse.
  • Implement CI/CD and DevOps practices for Databricks deployments.
  • Partner with data science teams on MLflow, MLOps, machine learning, and GenAI/LLM workloads.
  • Troubleshoot complex Databricks, Spark, Delta Lake, and pipeline issues.
  • Conduct architecture workshops and advise customers on Databricks best practices and roadmap.
  • Mentor engineering teams and serve as a trusted technical advisor to customer stakeholders.

Required Qualifications

  • 7+ years of experience in data engineering, data architecture, or cloud data platforms.
  • 3+ years of hands-on Databricks experience with multiple enterprise implementations.
  • Strong expertise in:
    • Databricks Lakehouse Platform
    • Delta Lake
    • Apache Spark
    • Unity Catalog
    • Databricks Workflows/Jobs
    • Databricks SQL
    • ETL/ELT and data engineering
  • Strong Python, SQL, and PySpark skills.
  • Experience with Azure Databricks, AWS Databricks, or Databricks on Google Cloud Platform.
  • Strong understanding of Spark performance tuning and distributed processing.
  • Experience with CI/CD, MLOps, and MLflow.
  • Experience with Databricks governance, security, and data architecture.
  • Strong customer-facing consulting, communication, and presentation skills.
  • U.S. work authorization without current or future visa sponsorship.

Preferred Qualifications

  • Databricks Certified Data Engineer Professional certification.
  • Databricks Solutions Architect certification.
  • Experience with Generative AI, LLMs, Vector Search, Model Serving, and Mosaic AI.
  • Experience with Structured Streaming and real-time data processing.
  • Experience migrating enterprise data warehouses/data lakes to Databricks.
  • Experience in consulting or professional services environments.
 

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