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Platform Monitor Jobs in Ridgewood, NY (NOW HIRING)

Monitor performance, ensure data integrity, and maintain system documentation. * Establishes and enforces governance frameworks, policies, and best practices for the platform. * Operationalize ...

Monitor performance, ensure data integrity, and maintain system documentation. * Establishes and enforces governance frameworks, policies, and best practices for the platform. * Operationalize ...

Monitoring and Troubleshooting: Assist in diagnosing platform issues, analyzing logs/metrics, and supporting stability efforts. Help maintain observability using Azure Monitor and Log Analytics ...

Help maintain observability using Azure Monitor and Log Analytics Monitor Databricks jobs, clusters, and infrastructure health. • Platform Reliability Support: Participate in troubleshooting ...

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Platform Monitor information

See Ridgewood, NY salary details

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How much do platform monitor jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for platform monitor in Ridgewood, NY is $65.50, according to ZipRecruiter salary data. Most workers in this role earn between $51.68 and $75.58 per hour, depending on experience, location, and employer.

Databricks Platform Engineer

New York, NY • On-site

ExlService Holdings, Inc.
IT Services • 10K+ employees

Full-time

Re-posted 26 days ago


ExlService Holdings rating

7.8

Company rating: 7.8 out of 10

Based on 8 frontline employees who took The Breakroom Quiz


Job description


We are looking for a Databricks Platform Manager/Engineer responsible for designing, administering, securing, and optimizing the enterprise Databricks platform on AWS. The ideal candidate will own the platform lifecycle, ensuring scalability, security, governance, cost optimization, and operational excellence while enabling data engineering, analytics, and AI teams to work efficiently.
This role focuses on platform engineering rather than data engineering or analytics development.
Responsibilities
Platform Administration
  • Design, deploy, and manage Databricks workspaces across Development, Test, UAT, and Production environments.
  • Establish workspace standards, networking, and environment isolation.
  • Manage platform upgrades, including Databricks Runtime (DBR) version planning, testing, and rollout.
  • Maintain platform availability, reliability, and performance.

Compute & Cluster Management
  • Create and manage cluster policies to enforce organizational standards.
  • Configure instance pools and job clusters.
  • Prevent oversized or non-compliant clusters.
  • Standardize cluster configurations across teams.
  • Optimize cluster startup times and resource utilization.

Security & Identity Management
  • Integrate Databricks with AWS IAM.
  • Configure and manage authentication and authorization.
  • Manage service principals, personal access tokens (PATs), and secret scopes.
  • Implement least-privilege access controls.
  • Support enterprise identity management and SSO.

Governance & Data Access
  • Administer Unity Catalog.
  • Manage catalogs, schemas, tables, and permissions.
  • Implement role-based access control (RBAC).
  • Enforce data governance and access policies.
  • Support audit and compliance requirements.

DevOps & CI/CD
  • Configure Git integration with Databricks Repos.
  • Support CI/CD pipelines for notebooks, workflows, and infrastructure.
  • Collaborate with DevOps teams on automated deployments.
  • Enable Infrastructure as Code (IaC) using Terraform where applicable.

Monitoring & Operations
  • Monitor workspace health, jobs, clusters, and platform performance.
  • Respond to incidents and perform root cause analysis.
  • Maintain operational dashboards and alerts.
  • Support production releases and platform maintenance activities.

Cost Optimization
  • Monitor Databricks usage and cloud spending.
  • Recommend cluster sizing and auto-scaling strategies.
  • Optimize job scheduling and compute utilization.
  • Track cost trends and recommend savings opportunities.

Compliance & Audit
  • Configure audit logging.
  • Ensure platform complies with enterprise security policies.
  • Support internal and external audits.
  • Maintain operational documentation and platform standards.

Qualifications
Required Skills
5-10 years of overall IT experience, including 3-5+ years of hands-on experience administering and managing Databricks platforms in production environments on AWS.
  • Databricks Platform
  • Workspace administration
  • Cluster management
  • Cluster policies
  • Instance pools
  • Job clusters
  • Databricks Runtime management
  • Workflows
  • Databricks Repos
  • Unity Catalog
  • Secret Scopes
  • Service Principals
  • Personal Access Tokens (PATs)
  • AWS
  • IAM
  • VPC fundamentals
  • EC2 concepts
  • S3
  • CloudWatch
  • KMS
  • Security Groups
  • Networking fundamentals
  • DevOps
  • Git
  • CI/CD
  • Terraform
  • Infrastructure as Code
  • Azure DevOps, GitHub Actions, or Jenkins
  • Monitoring
  • Platform monitoring
  • Incident management
  • Log analysis
  • Performance tuning
  • Cost optimization
  • Required Experience

Candidates should have hands-on experience with:
  • Managing enterprise Databricks platforms
  • Setting up multiple Databricks workspaces
  • Configuring Unity Catalog
  • AWS IAM integration
  • Cluster policy creation and governance
  • Runtime version upgrades
  • CI/CD implementation
  • Git integration
  • Platform monitoring and troubleshooting
  • Secrets management
  • Audit logging
  • Production support
  • Cost optimization initiatives

Preferred Qualifications
  • Experience managing large-scale Databricks environments (100+ users).
  • Experience supporting multiple business units or enterprise data platforms.
  • Hands-on experience with Terraform for Databricks infrastructure provisioning.
  • Knowledge of Lakehouse architecture and Delta Lake.
  • Experience with FinOps practices for cloud cost optimization.
  • Familiarity with data governance and security frameworks.

Nice to Have
  • Experience with AWS Organizations and Control Tower.
  • Knowledge of networking concepts for private connectivity (PrivateLink, VPC endpoints).
  • Experience with monitoring tools such as CloudWatch, Datadog, or Splunk.
  • Exposure to Apache Spark internals.
  • Experience supporting AI/ML workloads on Databricks.
  • Education
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

Certifications (Preferred)
  • Databricks Certified Data Engineer Professional or Databricks Certified Platform Administrator (if available).
  • AWS Certified Solutions Architect - Associate/Professional.
  • AWS Certified SysOps Administrator.
  • Terraform Associate certification.

What ExlService Holdings employees say

Pay

Hours and flexibility

Workplace

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