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Remote Azure Databricks Jobs in Spanaway, WA (NOW HIRING)

Senior DevOps Engineer

Seattle, WA · Remote

$133K - $170K/yr

Remote - USA The AES Group is hiring an experienced Senior DevOps Engineer to join our growing ... Support Azure cloud-native services, including Azure Databricks, for data engineering and AI/ML ...

Data Engineer

Seattle, WA · On-site +1

$130K - $150K/yr

... Databricks Lakehouse platform hosted in Microsoft Azure. In this role, you will be on the cutting ... Seattle candidates will have a hybrid remote/in-office schedule where you will work from our casual ...

Manager, Data Engineer (Remote)

Home, WA · Remote

$100K - $174K/yr

We unify internal and external data on modern cloud platforms-including Snowflake and Databricks within the Azure ecosystem-to produce reliable, analytics-ready data assets that support both ...

Manager, Data Engineer (Remote)

Home, WA · Remote

$100K - $174K/yr

We unify internal and external data on modern cloud platforms-including Snowflake and Databricks within the Azure ecosystem-to produce reliable, analytics-ready data assets that support both ...

Commercial Performance Lead Developer

Olympia, WA · Remote

$63.25 - $82.75/hr

Strong hands-on fluency with Databricks for data processing, transformation, and analytics ... Git, Azure DevOps). * Degree in a data, analytics, computer science, or related field - * 5+ years ...

Remote Azure Databricks information

What is a remote Azure Databricks?

Remote Azure Databricks jobs are positions where professionals use Azure Databricks—a cloud-based analytics platform optimized for big data and machine learning—while working from a remote location. These roles typically involve tasks like building data pipelines, analyzing large datasets, developing and deploying machine learning models, and collaborating with teams virtually. Remote Azure Databricks professionals need strong skills in Spark, Python or Scala, and a good understanding of cloud computing. They often work as data engineers, data scientists, or analytics specialists, leveraging the platform’s capabilities to deliver data-driven insights for organizations.

What skills and qualifications are needed to thrive as a remote Azure Databricks professional?

To thrive as a Remote Azure Databricks professional, you need strong expertise in data engineering, cloud computing, and proficiency in programming languages such as Python or Scala, typically supported by a relevant degree or certifications. Familiarity with Azure services, Databricks platform, Spark, and data pipeline orchestration tools is essential, often validated by Microsoft Azure or Databricks certifications. Excellent problem-solving, collaboration, and communication skills help you work effectively in distributed teams and convey complex technical concepts clearly. These skills and qualifications ensure robust data solutions, efficient remote teamwork, and the ability to leverage cloud analytics for business impact.

What are common challenges faced by remote Azure Databricks engineers, and how can they be managed?

Remote Azure Databricks engineers often encounter challenges related to collaboration and data security. Since Databricks projects typically involve large datasets and multiple stakeholders, coordinating work across time zones and ensuring secure data access can be complex. To manage these challenges, it's important to establish clear communication channels, use project management tools, and follow best practices in data governance. Regular team meetings and thorough documentation also help maintain alignment and ensure project success.

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

AspectRemote Azure DatabricksRemote Data Engineer
Required CredentialsAzure certifications, Spark/Databricks knowledgeData engineering certifications, SQL, cloud platform skills
Work EnvironmentCloud-based, collaborative platform for data analyticsData pipelines, database management, cloud environments
Industry UsageData analytics, AI, machine learning projectsData pipeline development, ETL processes

Remote Azure Databricks specialists focus on leveraging the Databricks platform for data analytics and machine learning, often working within cloud environments. Remote Data Engineers build and maintain data pipelines and infrastructure, frequently using cloud tools. While both roles require cloud and data skills, Azure Databricks roles are more centered on analytics and AI, whereas Data Engineers focus on data infrastructure and processing.

What cities near Spanaway, WA are hiring for Remote Azure Databricks jobs?

Cities near Spanaway, WA with the most Remote Azure Databricks job openings:

Senior DevOps Engineer

Seattle, WA • Remote

$133K - $170K/yr

Contractor

Re-posted 12 days ago


Job description

Job Title: Senior DevOps Engineer
Location: Remote - USA

The AES Group is hiring an experienced Senior DevOps Engineer to join our growing technology team and drive enterprise-scale cloud infrastructure modernization initiatives. This is an exciting opportunity for a highly skilled DevOps professional with expertise in Terraform, Kubernetes, Python automation, and Azure cloud technologies, including Azure Databricks, to build scalable, secure, and reliable infrastructure supporting advanced AI/ML platforms.

Why Join The AES Group?

  • Work on cutting-edge cloud transformation and AI/ML infrastructure projects
  • Opportunity to contribute to GenAI and Azure Cognitive Services environments
  • Collaborate with high-performing engineering teams on enterprise-scale initiatives
  • Hybrid work flexibility based in Seattle, WA
  • Long-term project engagement with strong career growth potential

Key Responsibilities:

  • Design, deploy, and manage scalable, secure, and reliable infrastructure solutions using Terraform.
  • Lead migration efforts from ARM templates and PowerShell-based provisioning to Terraform-based Infrastructure as Code (IaC).
  • Develop and maintain reusable IaC modules to enable version-controlled, repeatable deployments.
  • Implement, manage, and optimize Kubernetes clusters supporting containerized microservices environments.
  • Partner with development teams to deploy, scale, and troubleshoot applications in Kubernetes ecosystems.
  • Automate provisioning, deployment, and operational workflows using Python scripting.
  • Build and maintain CI/CD pipelines to streamline software delivery and release cycles.
  • Integrate infrastructure provisioning seamlessly into CI/CD workflows.
  • Design and maintain scalable infrastructure environments for AI/ML and GenAI platforms.
  • Deploy and manage Docker containerized applications orchestrated through Kubernetes.
  • Support Azure cloud-native services, including Azure Databricks, for data engineering and AI/ML workload orchestration.
  • Enable secure and efficient integration of AI/ML models into enterprise production platforms.
  • Establish monitoring, logging, and alerting systems to maintain infrastructure health and performance.
  • Implement security best practices to ensure compliance, governance, and data privacy standards.

Required Skills & Qualifications:

  • 10+ years of experience in DevOps, Infrastructure Engineering, or Cloud Platform Engineering.
  • Strong hands-on expertise with Terraform, including migration from ARM/PowerShell to Terraform.
  • Deep experience managing Kubernetes clusters and deploying containerized microservices.
  • Strong proficiency in Python scripting for automation and workflow optimization.
  • Solid experience with Docker and container orchestration technologies.
  • Hands-on experience designing and maintaining CI/CD pipelines.
  • Strong understanding of Infrastructure as Code (IaC) principles and best practices.
  • Proven experience with Microsoft Azure cloud platform services.
  • Required hands-on experience with Azure Databricks for cloud data processing and AI/ML platform integration.
  • Experience designing and supporting scalable infrastructure for AI/ML environments.
  • Knowledge of Azure Cognitive Services and GenAI project deployments is highly preferred.
  • Strong understanding of cloud security, compliance, and monitoring frameworks.
  • Excellent communication and collaboration skills in cross-functional engineering teams.

Preferred Qualifications:

  • Experience working as a platform engineer in AI/ML-driven environments.
  • Exposure to deployment automation for Azure Cognitive Services and GenAI workloads.
  • Prior involvement in enterprise cloud modernization initiatives.

Ready to make an impact? Apply now and join us on our journey!