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Dataops Jobs in New York (NOW HIRING)

Octus

Software Engineer

New York, NY · On-site

$110K - $120K/yr

The DataOps Engineering team is focused on internal user-facing applications that build and maintain the core internal web and data platform, enabling users to ingest key data that is core to the ...

Watershed Ventures

Software Engineer

Manhattan, NY · On-site

$110 - $120/hr

The DataOps Engineering team is focused on internal user-facing applications that build and maintain the core internal web and data platform, enabling users to ingest key data that is core to the ...

Octus

Software Engineer

New York, NY · On-site

$110K - $120K/yr

The DataOps Engineering team is focused on internal user-facing applications that build and maintain the core internal web and data platform, enabling users to ingest key data that is core to the ...

Rearc

Senior Data Engineer

New York, NY · On-site

$160K - $200K/yr

You bring a DataOps mindset: CI/CD for data pipelines, automated testing, observability, and infrastructure-as-code are standard practice for you, not afterthoughts. * Your experience spans ETL/ELT ...

Selective Insurance

Data & Analytics Architect

Short Hills, NJ · On-site

$69.25 - $89.25/hr

Proposes actions to realize opportunities and advocates for DevOps/DataOps opportunities. Qualifications : Required : • Bachelor's Degree in Computer Science, or other related field, or equivalent ...

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How much do dataops jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for dataops in New York is $25.30, according to ZipRecruiter salary data. Most workers in this role earn between $19.18 and $26.30 per hour, depending on experience, location, and employer.

What is a DataOps?

DataOps, short for Data Operations, is a set of practices, processes, and technologies that combine data engineering, data integration, and DevOps methodologies to improve the quality and speed of data analytics. DataOps aims to streamline the flow of data from source to value, enabling organizations to deliver reliable, high-quality data to stakeholders more efficiently. This approach emphasizes collaboration, automation, and monitoring throughout the data lifecycle to reduce errors and shorten development cycles. The ultimate goal of DataOps is to create an agile data pipeline that adapts quickly to changing business needs.

How does a DataOps professional typically collaborate with data engineers, analysts, and other IT teams?

DataOps professionals play a key role in bridging the gap between data engineering, analytics, and IT by facilitating efficient, automated workflows and ensuring data quality across the pipeline. They often work closely with data engineers to streamline data integration and deployment processes, while collaborating with analysts to support timely access to reliable data. Regular communication and cross-functional teamwork are essential, as DataOps is responsible for implementing best practices that help different teams deliver insights faster and with fewer errors. This collaborative environment also encourages continuous feedback and process improvement.

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

To thrive as a DataOps Engineer, you need expertise in data engineering, automation, cloud platforms, and a solid understanding of CI/CD pipelines, typically backed by a degree in computer science or related fields. Familiarity with tools like Apache Airflow, Kubernetes, Docker, Jenkins, and cloud services such as AWS, GCP, or Azure is commonly required, along with knowledge of scripting languages like Python or Bash. Strong collaboration, problem-solving, and communication skills help DataOps professionals work effectively across data, development, and operations teams. These abilities ensure reliable, scalable, and efficient data infrastructure, enabling organizations to quickly deliver high-quality data solutions.

What is the difference between Dataops vs Data Engineer?

AspectDataopsData Engineer
Primary FocusAutomating data workflows, deployment, and operational efficiencyBuilding and maintaining data pipelines, storage, and infrastructure
Skills & CertificationsDevOps tools, scripting, cloud platforms, CI/CD practicesSQL, ETL tools, cloud platforms, programming (Python, Scala)
Work EnvironmentCollaborates with DevOps, data teams, and operationsWorks closely with data scientists, analysts, and infrastructure teams
Industry UsageUsed in organizations focusing on data deployment and automationUsed in data infrastructure development and data pipeline creation

While both Dataops and Data Engineers work with data infrastructure, Dataops emphasizes automation, deployment, and operational efficiency, whereas Data Engineers focus on building and maintaining data pipelines and storage systems. Understanding these differences helps organizations assign the right roles for their data needs.

What are popular job titles related to Dataops jobs in New York?

For Dataops jobs in New York, the most frequently searched job titles are:

What job categories do people searching Dataops jobs in New York look for?

The top searched job categories for Dataops jobs in New York are:

Dataops jobs near you
Infographic showing various Dataops job openings in New York as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $52,634 per year, or $25.3 per hour.

CSOC DataOps Engineer: Security Telemetry & Ingestion

Bloomberg L.P.

Manhattan, NY • On-site

$190 - $260/hr

Other

Posted 4 days ago

Bloomberg rating

9.4

Company rating: 9.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

11th of 245 rated software companies

Job description

Bloomberg L.P. is seeking a candidate for a critical role focused on Security Data Management in New York. This position involves overseeing the onboarding of security logs for effective CSOC monitoring and detection, while ensuring the continuity and quality of log flows across systems.

Ideal candidates have 4-6 years experience in security operations or technology, strong skills in log management and SIEM platforms, as well as excellent communication skills to bridge technical concepts.

The role offers a competitive salary ranging from $190,000 to $260,000 annually, along with a comprehensive benefits package.

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What Bloomberg employees say

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About Bloomberg

Sourced by ZipRecruiter

Bloomberg runs on data. As the Data Management & Analytics team within Engineering, we support our organization's needs around managing data efficiently. The vision of the team is to build solutions that drive data quality, data dictionary, data stewardship, data lineage, reference, and master data management across various data domains (prospect, customer, vendor, material etc.). We partner with business teams across the organization in addressing their data needs and ultimately helping run business operations efficiently and make improved decisions.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1981

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