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Databricks Admin Jobs in Pennsylvania (NOW HIRING)

Bayforce

Azure Databricks Admin

Philadelphia, PA · On-site

Azure Databricks Admin Employment Type: Contract Duration: 6 months to start, with chance of extension up to 18 months Preferred Location: 4 days per week onsite in Wilmington, DE/Philadelphia PA ...

Infosys

Databricks Data Operation Engineer

Philadelphia, PA · On-site

$70K - $94K/yr

Preferred Skill and Experience Root cause (RCA) analysis and troubleshooting Runbook and SOP development Databricks and ADF platform admin Security, access management Additional Required ...

Geisinger Health

Senior Platform Data Engineer

Danville, PA · On-site +1

$121K - $164K/yr

Databricks workspace configuration and Unity Catalog governance. * Cluster policies, compute management, and cost monitoring. * Manges user/group management and access control. * Administrator for ...

Allocore

Senior Database Engineer (Hybrid)

Mechanicsburg, PA · On-site

$100K - $136K/yr

Design, implement, administer, and support database platforms including Aurora PostgreSQL, Amazon DocumentDB, Amazon Redshift, Databricks, ElastiCache, Oracle, and MSSQL where applicable. * Knowledge ...

Deloitte

Kinaxis Manager

Philadelphia, PA

... 1, Administrator Level 1, and Integration Level 1 * Experience with Talend or other extract, transform, load (ETL) tools, including Google Cloud Dataflow, Azure Data Factory, or Databricks

All JobsDatabricks Admin JobsDatabricks Admin Jobs in Pennsylvania

Databricks Admin information

What are Databricks Admins?

Databricks Admins are IT professionals responsible for managing and configuring the Databricks platform within an organization. They handle user access, workspace setup, cluster management, security policies, and integration with cloud services. Their role is crucial in ensuring that the Databricks environment runs smoothly, securely, and efficiently for data teams. Admins also monitor resource usage, troubleshoot issues, and implement best practices for data processing and analytics workflows.

What are some common challenges a Databricks Admin faces when managing large-scale data pipelines?

As a Databricks Admin, one of the primary challenges is ensuring optimal cluster performance and resource utilization, especially when handling large and complex data pipelines. Admins must monitor job execution, manage user access, and troubleshoot issues related to data connectivity, cluster failures, or slow-running jobs. Additionally, maintaining data security and compliance across collaborative teams can be demanding, as it requires fine-tuning permissions and enforcing organizational policies. Strong communication with data engineers and analysts is essential to proactively address problems and optimize workflows.

What are the key skills and qualifications needed to thrive as a Databricks Admin, and why are they important?

To thrive as a Databricks Admin, you need a solid background in data engineering, cloud computing, and distributed systems, often supported by a degree in computer science or related field. Proficiency in Databricks platform management, Spark, Azure or AWS services, and relevant certifications like Databricks Certified Associate Developer are typically required. Strong problem-solving, communication, and collaboration skills help in effectively managing resources and supporting data teams. These skills ensure optimal platform performance, secure data workflows, and support for analytics initiatives across the organization.

What is the difference between Databricks Admin vs Data Engineer?

AspectDatabricks AdminData Engineer
CredentialsDatabricks certifications, cloud platform knowledgeProgramming skills, cloud certifications, data modeling
Work EnvironmentCloud-based Databricks platform, administrative tasksData pipelines, ETL processes, coding environments
Employer & IndustryTech companies, data-driven organizations using DatabricksOrganizations building data infrastructure, analytics teams
Search & Comparison IntentUnderstanding administrative roles in DatabricksData pipeline development and data architecture

While both roles work within data platforms, a Databricks Admin primarily manages and maintains the Databricks environment, focusing on platform configuration and user access. In contrast, a Data Engineer builds and maintains data pipelines, often utilizing Databricks for data processing. Both roles require cloud platform knowledge, but their core responsibilities differ significantly.

What are popular job titles related to Databricks Admin jobs in Pennsylvania? For Databricks Admin jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Databricks Admin jobs in Pennsylvania look for? The top searched job categories for Databricks Admin jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Databricks Admin jobs? Cities in Pennsylvania with the most Databricks Admin job openings:
Databricks Admin jobs near you
Infographic showing various Databricks Admin job openings in Pennsylvania as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, 1% Temporary, and 5% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution.

Azure Databricks Admin

Bayforce

Philadelphia, PA • On-site

Other

Posted 9 days ago

Job description

Role Title: Azure Databricks Admin

Employment Type: Contract

Duration: 6 months to start, with chance of extension up to 18 months

Preferred Location: 4 days per week onsite in Wilmington, DE/Philadelphia PA area

Role Description:

Urgent need for an Azure Databricks admin with 5 years experience and strong Terraform skills for ongoing support onsite in Wilmington. The position is for ongoing operational support, not a short-term project.

Requirements:

Minimum 4+ years of hands on experience administering Azure Databricks platforms in an enterprise environment.

Proven experience configuring and managing Azure Databricks platform components, including:

  • Clusters: autoscaling configurations, instance pools, cluster policies, and performance optimization
  • Jobs and Workflows: scheduling, concurrency controls, retries, alerts, and notifications
  • Workspace assets: notebooks, Git repos, libraries, init scripts, and secret scopes
  • Strong experience with Unity Catalog and implementation of enterprise data governance models, including fine grained access controls and catalog level security.
  • Experience with Databricks automation and deployment tooling, including:
  • Databricks CLI
  • Databricks REST APIs
  • Databricks Asset Bundles (DAB)
  • Experience integrating Databricks with BI Tools/analytics platforms.
  • Solid understanding of data engineering patterns, Spark based workloads, and techniques for tuning performance and optimizing resource usage.
  • Working knowledge of Microsoft Azure fundamentals, including:
  • Identity and access management using RBAC, service principals, and managed identities
  • Azure Data Lake Storage Gen2 (ADLS Gen2), Azure Key Vault, Azure Monitor, and Log Analytics
  • Azure networking concepts such as VNets, private endpoints, and DNS resolution
  • Proven expertise with Terraform, including:
  • Modular design patterns
  • Remote state management
  • Multi environment deployment strategies
  • Secure infrastructure as code practices
  • Strong experience building and maintaining CI/CD pipelines using GitLab CI/CD, including:
  • YAML based pipeline definitions
  • Runner configuration
  • Environment promotion strategies
  • Approval gates and controlled deployments
  • Demonstrated experience supporting compliance driven and regulated environments, including:
  • Audit evidence collection and documentation
  • Periodic access reviews
  • Change management and release controls
  • Nice to Have experience on MLOps, including:
  • Experience supporting machine learning workloads on Azure Databricks
  • Familiarity with MLflow for experiment tracking, model registry, and lifecycle management
  • Exposure to MLOps pipelines, including model training, validation, and deployment automation
  • Understanding of model governance, versioning, and promotion across environments

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