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Databricks Engineer Jobs in Queens, NY (NOW HIRING)

TheStaffed

Senior Software Engineer - Databricks

New York, NY · On-site

$134K - $176K/yr

... Software Engineer with 8-10 years of experience to rebuild and develop applications for the Direct Investment Unit, focusing on data pipelines and platform modernization using Databricks while ...

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Databricks Engineer information

See Queens, NY salary details

$62.1K

$116.5K

$211.8K

How much do databricks engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for databricks engineer in Queens, NY is $116,484.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $138,300.00 per year, depending on experience, location, and employer.

What is a Databricks engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

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

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.

What are some common challenges faced by Databricks engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $90,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, and data engineering can earn higher compensation, often including bonuses and benefits.

Is a Databricks engineer in demand?

Databricks engineers are in high demand due to the growing adoption of cloud-based data analytics and machine learning platforms. They typically require skills in Spark, SQL, and cloud environments like AWS or Azure, making them valuable in data-driven organizations across various industries.

What are popular job titles related to Databricks Engineer jobs in Queens, NY?

For Databricks Engineer jobs in Queens, NY, the most frequently searched job titles are:

What job categories do people searching Databricks Engineer jobs in Queens, NY look for?

The top searched job categories for Databricks Engineer jobs in Queens, NY are:

What cities near Queens, NY are hiring for Databricks Engineer jobs?

Cities near Queens, NY with the most Databricks Engineer job openings:

Databricks Engineer jobs near you

Databricks Platform Manager/Engineer

Prama Innovations India Pvt. Ltd.

Manhattan, NY • On-site

Other

Posted 17 days ago

Job description

Job Title: Databricks Platform Manager/Engineer
Location: NY (Hybrid Onsite)
Type: Contract
 
Job Summary
We are looking for a Databricks Platform Manager/Engineer with strong hands-on experience administering enterprise Databricks environments on AWS. The role focuses on platform administration, workspace and cluster management, Unity Catalog, AWS IAM, security/governance, Terraform/IaC, CI/CD, monitoring, and cost optimization. Ideal candidates will have 3–5+ years of production Databricks platform administration experience and a strong AWS/cloud infrastructure background.
Key Responsibilities
  • Administer and support Databricks workspaces across Dev, Test, UAT, and Production.
  • Manage clusters, cluster policies, instance pools, job clusters, and Databricks Runtime upgrades.
  • Administer Unity Catalog, catalogs, schemas, permissions, and RBAC.
  • Manage AWS IAM integration, SSO, service principals, secrets, and access controls.
  • Implement and support Terraform/IaC and CI/CD for Databricks platform deployments.
  • Manage Git/Databricks Repos and automated deployment processes.
  • Monitor platform health, performance, jobs, clusters, and production environments.
  • Troubleshoot platform issues, incidents, and performance problems.
  • Support audit logging, security, governance, and compliance requirements.
  • Identify opportunities for Databricks and AWS cost optimization.
  • Partner with Data Engineering, DevOps, Cloud, Security, and Infrastructure teams.
Required Skills
  • Strong hands-on Databricks Platform Administration
  • Databricks Workspace Management
  • Cluster Management & Cluster Policies
  • Unity Catalog
  • Databricks Runtime
  • Service Principals, Secrets & PATs
  • AWS IAM
  • AWS S3, VPC, EC2, KMS, Security Groups
  • Terraform / Infrastructure as Code
  • Git and CI/CD
  • Azure DevOps, GitHub Actions, or Jenkins
  • Platform Monitoring & Troubleshooting
  • Production Support
  • Cost Optimization
Preferred
  • Experience supporting enterprise Databricks environments with 100+ users
  • Experience with AWS PrivateLink / VPC Endpoints
  • AWS Organizations / Control Tower
  • CloudWatch, Datadog, or Splunk
  • Delta Lake / Lakehouse architecture
  • Exposure to Spark internals
  • Experience supporting Databricks AI/ML workloads
  • Databricks or AWS certifications

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