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Azure Databricks Jobs in Washington (NOW HIRING)

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Senior Data Engineer

Washington, DC · Remote

$120K - $175K/yr

Databricks Spark Pipelines & ETL Engineering: Build and scale distributed PySpark and Spark SQL pipelines on Azure Databricks to ingest raw scheduled feeds (nightly/weekly flat files or database ...

Navy Federal Credit Union

Principal Data Engineer

Vienna, VA · On-site

$114K - $138K/yr

Design, develop, and optimize scalable batch, near real-time, and real-time data pipelines using Spark, Python, SQL, Databricks, Microsoft Fabric, Azure Data Factory, and related Azure cloud services.

System One

Data Management Specialist II

Washington, DC · On-site

$52.09/hr

Work with data teams to build scalable ETL (Extract, Transform, Load) processes using Azure Databricks. * Create and maintain Power BI reports, dashboards, and data visualizations that provide ...

System One

Data Management Specialist II

Washington, DC · On-site

$52.09/hr

Work with data teams to build scalable ETL (Extract, Transform, Load) processes using Azure Databricks. * Create and maintain Power BI reports, dashboards, and data visualizations that provide ...

System One

Data Management Specialist II

Washington, DC · On-site

$52.09/hr

Work with data teams to build scalable ETL (Extract, Transform, Load) processes using Azure Databricks. * Create and maintain Power BI reports, dashboards, and data visualizations that provide ...

System One

Data Management Specialist II

Washington, DC · On-site

$52.09/hr

Work with data teams to build scalable ETL (Extract, Transform, Load) processes using Azure Databricks. * Create and maintain Power BI reports, dashboards, and data visualizations that provide ...

MDAEdge

Medicaid Data Systems Analyst

Washington, DC · On-site

... for Azure Data Factory and Databricks. • Map raw MMIS schemas to target Data Warehouse formats for BI tools. Qualifications : Required : • bachelor's degree • 5+ years of relevant experience ...

Initiate Government Solutions

Data Engineer

Washington, DC · On-site

$126K - $152K/yr

The ideal candidate will possess hands-on experience with Azure Data Factory (ADF), Azure Databricks, and Apache Kafka, along with expertise in modern data engineering methodologies, DevSecOps ...

Quantum Vision

Data Architect

Vienna, VA · On-site

$64 - $82.25/hr

Databricks: 5 Years * Python Scripting: 5 Years * Azure DevOps: 3 Years * SharePoint: 3 Years * Strong interpersonal skills and the ability to work effectively with diverse teams * Experience in ...

ECS

Sr. Databricks Consultant

Fairfax, VA · On-site +1

$175K - $250K/yr

Integrate Databricks with cloud platforms (AWS, Azure, or GCP). * Implement data governance, security, and compliance standards. * Collaborate with data scientists, analysts, and business ...

DLA Piper

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Design and implement data pipelines using Azure data technologies (e.g., Azure Data Factory, Azure Databricks, Azure Event Hubs, SSIS) to ingest, process, and deliver data from sources such as APIs ...

Dlapiper

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Design and implement data pipelines using Azure data technologies (e.g., Azure Data Factory, Azure Databricks, Azure Event Hubs, SSIS) to ingest, process, and deliver data from sources such as APIs ...

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Azure Databricks information

What is an Azure Databricks?

An Azure Databricks job is a way to run a notebook, JAR, Python script, or other workload in an automated or scheduled manner on an Azure Databricks cluster. Jobs allow users to orchestrate data processing, machine learning tasks, or ETL workflows efficiently. They can be triggered manually, on a schedule, or in response to events, enabling streamlined data pipeline management. Jobs also support multi-task workflows, allowing dependencies between different tasks.

What does an Azure Databricks do?

A typical day for an Azure Databricks professional involves designing, developing, and maintaining data pipelines, collaborating with data scientists and business analysts to transform raw data into actionable insights. You may spend time configuring Spark clusters, optimizing query performance, ensuring data security, and troubleshooting data workflow issues. Regular meetings with stakeholders and team members are common to align on project requirements and report progress. This role often offers a mix of independent technical work and team collaboration, making it both dynamic and engaging.

What are the key skills and qualifications needed for an Azure Databricks?

To thrive as an Azure Databricks professional, you need expertise in big data analytics, data engineering, and proficiency with SQL, Python, and Apache Spark, typically supported by a degree in computer science or a related field. Familiarity with the Azure cloud ecosystem, Databricks platform tools, and advantageous certifications like Azure Data Engineer Associate are highly valuable. Strong problem-solving skills, collaboration, and the ability to communicate technical concepts clearly help set you apart in this role. These abilities are crucial for designing and optimizing scalable data solutions and effectively working within cross-functional data teams.

Are Azure Databricks in high demand?

Azure Databricks professionals are in high demand due to the increasing adoption of cloud-based data analytics and machine learning solutions. Skills in Spark, Python, and cloud environments enhance job prospects, with many organizations seeking expertise in managing large-scale data workflows on Azure. The role often requires familiarity with data engineering, data science, and cloud certifications.

Is Azure Databricks difficult to learn?

Azure Databricks is a cloud-based data analytics platform that combines Apache Spark with Azure services, and learning it involves understanding Spark concepts, data engineering, and cloud environment management. While it has a learning curve for beginners, familiarity with programming languages like Python or Scala and basic data processing skills can facilitate the learning process.

What is a job in Azure Databricks?

A job in Azure Databricks refers to an automated task or set of tasks that run on the platform, such as data processing, machine learning model training, or data pipeline execution. These jobs are scheduled and managed through the Azure Databricks workspace, often requiring knowledge of Spark, Python, Scala, or SQL. They enable users to automate workflows and handle large-scale data analytics efficiently.

What is the salary of an Azure Databricks engineer?

The salary of an Azure Databricks engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and certifications. Professionals with strong skills in Spark, cloud computing, and data engineering can expect higher compensation. Salaries may also vary based on company size and industry demand.

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

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

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

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

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

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

What cities in Washington are hiring for Azure Databricks jobs?

Cities in Washington with the most Azure Databricks job openings:

Azure Databricks jobs near you
Infographic showing various Azure Databricks job openings in Washington as of August 2026, with employment types broken down into 53% Full Time, and 47% Contract. Highlights an 100% In-person job distribution.

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Alexandria, VA

SiloSmashers
Business Management Consulting • 11 - 50 employees
Learn more about SiloSmashersexternal

Full-time

Re-posted yesterday

Job description

About the Role

We're looking for a Senior ML Engineer to join a product team and help build, train, and ship machine learning models that power real user-facing features. This is a hands-on role for someone who enjoys owning the full lifecycle of a model - from experimentation through production deployment and monitoring - and who is comfortable working closely with product and engineering partners in a hybrid office environment.

What You'll Do
  • Design, build, and train machine learning models to solve product problems, iterating from prototype to production.
  • Own the MLOps lifecycle: experiment tracking, reproducible training pipelines, model versioning, deployment, and monitoring.
  • Partner directly with product managers and engineers embedded in your team to translate business requirements into ML solutions.
  • Deploy and maintain models on Azure (Azure ML, Azure Databricks, and/or AKS), ensuring reliability and cost efficiency at scale.
  • Monitor model performance in production, diagnose drift and degradation, and drive retraining and improvement cycles.
  • Write clean, well-tested, production-grade Python code and contribute to shared ML tooling and best practices.
  • Collaborate cross-functionally to define success metrics, run experiments (A/B tests), and communicate results to technical and non-technical stakeholders.
What We're Looking For
  • 6–10 years of professional experience in software/ML engineering, with a strong track record of building and training ML models.
  • Deep hands-on expertise in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
  • Practical MLOps experience - tools such as MLflow, Kubeflow, or Airflow for pipelines, tracking, and deployment.
  • Required: Certified Azure experience (e.g., Microsoft Certified: Azure AI Engineer Associate / AI-102), plus hands-on production experience with Azure ML, Azure Databricks, or AKS.
  • Solid understanding of the full ML lifecycle: data preparation, training, evaluation, deployment, and monitoring.
  • Strong communication skills and comfort working embedded within a cross-functional product team.
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Nice to Have
  • Experience with large language models (LLMs) or generative AI APIs (e.g., Claude, OpenAI, Azure OpenAI Service).

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