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Remote Dataops Engineer Jobs in Hackensack, NJ (NOW HIRING)

Peloton

Data Engineering Manager

New York, NY · On-site +1

This role will be hybrid, not remote. YOUR DAILY IMPACT AT PELOTON * Lead the DataOps function within the Data Engineering team, driving operational maturity, platform reliability, and process ...

Indicium AI

Databricks Data Engineer (Remote)

New York, NY · On-site +1

$120K - $160K/yr

Disseminating DevOps and DataOps best practices within the team. * Collaborate with teams to deliver data solutions that meet business needs. * Research and implement new technologies and tools to ...

Indicium AI

Databricks Data Engineer (Remote)

New York, NY · On-site +1

$120K - $160K/yr

Disseminating DevOps and DataOps best practices within the team. * Collaborate with teams to deliver data solutions that meet business needs. * Research and implement new technologies and tools to ...

All JobsDataops Engineer JobsRemote Dataops Engineer JobsRemote Dataops Engineer Jobs in Hackensack, NJ

Remote Dataops Engineer information

See Hackensack, NJ salary details

$41.4K

$126.4K

$208.9K

How much do remote dataops engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for remote dataops engineer in Hackensack, NJ is $126,367.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $165,200.00 per year, depending on experience, location, and employer.

What is the difference between Remote Dataops Engineer vs Data Engineer?

AspectRemote Dataops EngineerData Engineer
CredentialsBS in CS, Data Science, or related; certifications like AWS, GCP, or AzureSimilar credentials; often with additional database or software engineering certifications
Work EnvironmentRemote or hybrid, collaborative teams, cloud platformsRemote or on-site, data-focused teams, cloud and on-prem infrastructure
Industry UsageTech, finance, healthcare, e-commerceTech, finance, retail, telecom
Search & Comparison IntentUnderstanding roles in data operations, cloud deployment, automationFocus on data pipeline development, database management, ETL processes

The Remote Dataops Engineer and Data Engineer roles share many credentials and work environments, often overlapping in cloud and data infrastructure. However, Data Engineers typically focus more on building and maintaining data pipelines and databases, while Dataops Engineers emphasize automating deployment, monitoring, and optimizing data workflows in cloud environments.

What is a Remote DataOps Engineer?

A Remote DataOps Engineer is a technology professional who works remotely to manage, automate, and optimize data pipelines and processes within an organization. Their main goal is to streamline the flow of data between various systems, ensuring the availability, quality, and security of data for analytics and business operations. They collaborate closely with data engineers, analysts, and IT teams to develop efficient workflows, automate repetitive tasks, and monitor data infrastructure performance. By working remotely, they leverage cloud-based tools and communication platforms to support distributed teams and global data operations.

How do Remote DataOps Engineers typically collaborate with cross-functional teams to ensure smooth data pipeline operations?

Remote DataOps Engineers often work closely with data engineers, analysts, and DevOps teams using collaboration tools like Slack, Jira, and GitHub. Regular virtual meetings and documentation are essential to align on pipeline requirements, monitor data quality, and resolve issues quickly. Clear communication and proactive status updates help build trust with stakeholders and ensure that data infrastructure supports business needs efficiently, even when working remotely.

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

To thrive as a Remote DataOps Engineer, you need expertise in data engineering, automation, and pipeline management, typically backed by a degree in computer science or a related field. Familiarity with tools like Apache Airflow, Kubernetes, CI/CD systems, and cloud platforms such as AWS or Azure is highly valued, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills are crucial for managing distributed teams and complex data workflows. These skills and qualities ensure efficient, reliable, and scalable data infrastructure essential for modern data-driven organizations.
What are popular job titles related to Remote Dataops Engineer jobs in Hackensack, NJ? For Remote Dataops Engineer jobs in Hackensack, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Dataops Engineer jobs in Hackensack, NJ look for? The top searched job categories for Remote Dataops Engineer jobs in Hackensack, NJ are:
What cities near Hackensack, NJ are hiring for Remote Dataops Engineer jobs? Cities near Hackensack, NJ with the most Remote Dataops Engineer job openings:
Remote Dataops Engineer jobs near you
Data Engineering Manager

Data Engineering Manager

Peloton

New York, NY • On-site, Remote

Other

Posted 9 days ago

Job description

ABOUT THE ROLE

Peloton is looking for a talented Data Engineering Manager to join the Data Engineering team. In this role, you will lead the DataOps function, driving operational excellence across our data platforms while managing the successful delivery of data initiatives through a combination of internal and offshore engineering resources.

You will work closely with business stakeholders, engineering teams, analytics partners, and platform owners to ensure our data ecosystem remains reliable, scalable, and well-governed. This role combines technical leadership, operational management, and stakeholder engagement, to help support Peloton's growing data and AI needs.

This role will be hybrid, not remote.

YOUR DAILY IMPACT AT PELOTON
  • Lead the DataOps function within the Data Engineering team, driving operational maturity, platform reliability, and process improvements
  • Manage and mentor offshore engineering resources, providing technical guidance, performance feedback, and delivery oversight
  • Partner with stakeholders across multiple business functions to gather requirements, prioritize work, and ensure successful delivery of data solutions
  • Own intake, prioritization, and execution processes for DataOps requests and operational support activities
  • Drive adoption of data engineering standards, ETL best practices, documentation requirements, and operational procedures
  • Serve as an operational owner for key data platforms, including Airflow, Airbyte, and Looker, owning platform governance activities such as user access reviews, compliance reviews, audit support, and operational controls
  • Coordinate incident management, root cause analysis, monitoring, alerting, and operational readiness efforts across the data platform
  • Help shape the long-term operating model for the Data Engineering team as Peloton continues to scale its data and AI initiatives
YOU BRING TO PELOTON
  • 5+ years of experience in data engineering, analytics engineering, software engineering, or related technical roles
  • 2+ years of experience leading technical teams, managing engineering projects, or coordinating offshore/vendor resources
  • Strong understanding of modern data engineering architectures, ETL/ELT patterns, and data platform operations
  • Hands-on working experience with data orchestration and integration platforms such as Airflow, Airbyte, DBT, or similar technologies
  • Proven ability to translate business requirements into technical solutions and coordinate delivery across multiple stakeholders
  • Experience designing and supporting monitoring, alerting, incident response, and operational support processes
  • Excellent communication, prioritization, and organizational skills with the ability to manage competing priorities
  • Strong SQL and data analysis skills, ideally with BigQuery
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. Advanced degree preferred
BONUS
  • Experience administering or supporting compliance auditing for Looker, BigQuery, or other modern cloud analytics platforms
  • Experience managing distributed or offshore engineering teams
  • Experience building and scaling DataOps or platform operations functions
  • Experience implementing data quality, observability, lineage, or governance solutions
  • Experience supporting AI, machine learning, or self-service analytics initiatives
  • Experience working in Agile/Scrum environments and managing cross-functional technical programs

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