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Data Ops Manager Jobs in New York (NOW HIRING)

Neon Mobile, Inc

Data Ops Lead

New York, NY · On-site +1

$150K - $190K/yr

As a Data Ops Lead, you'll own the end-to-end journey that takes raw recordings from our growing ... Structuring and managing the data deals that turn our recordings into revenue * Holding every ...

Bloomberg L.P.

CSOC Data Ops Specialist

Manhattan, NY · On-site

$190 - $260/hr

Primary Focus - Security Data Management * Own and drive the end to end onboarding of security logs required by CSOC monitoring, detection, and investigation platforms. * Partner directly with system ...

Kalshi Inc

Creative Ops Manager

New York, NY · On-site

$100K - $170K/yr

Project & Timeline Management (35%) * Own end-to-end project management for all creative work ... This salary range is based on the current available market data, and represents the expected salary ...

Biograph International, Inc

CX Ops Manager

New York, NY · On-site

$110K - $150K/yr

As a CX Ops Manager, you will play a key role in building and formalizing Biograph's customer ... Work with a forward-thinking team that merges the latest in health technology, data science, and ...

Bidease

Product Ops Manager

New York, NY · On-site

$115K - $130K/yr

We work with top brands, agencies, and app developers to drive measurable growth through data ... Own end-to-end campaign management , from client onboarding to full campaign lifecycle execution ...

Medidata Solutions

Senior Data Engineer

Iselin, NJ · On-site

$96K - $128K/yr

Our Data Ops team empowers data-driven features across Factorial by providing advanced ingestion ... Engage with stakeholders from managers to product teams, translating monitoring and analytics ...

Profound

People Ops Manager

New York, NY · On-site

$130K - $190K/yr

Maintain Rippling as the source of truth for people data, ensuring accuracy across the employee ... Manage payroll, benefits administration, open enrollment, and compliance across our global employee ...

Bidease

Product Ops Manager

New York, NY · On-site +1

$115K - $130K/yr

We work with top brands, agencies, and app developers to drive measurable growth through data ... Own end-to-end campaign management , from client onboarding to full campaign lifecycle execution ...

MSD

Dir , Commercial Data Capability

Rahway, NJ · On-site

... ops, GenAI infra) thatCore data domains/solutions and the Emerging business solutions teams will ... Data Quality & Business Rules Management, Innovation Capabilities, Data Operations, and ...

3ds

Senior Data Engineer

Iselin, NJ · On-site

$96K - $128K/yr

Our Data Ops team empowers data-driven features across Factorial by providing advanced ingestion ... Engage with stakeholders from managers to product teams, translating monitoring and analytics ...

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Data Ops Manager information

What is a Data Ops manager?

Data Ops Managers are professionals responsible for overseeing the processes, tools, and teams involved in managing and optimizing data operations within an organization. They ensure the smooth flow, quality, and accessibility of data across various platforms and departments. Their role often includes automating data pipelines, implementing data governance practices, and collaborating with data engineers, analysts, and business stakeholders to support data-driven decision making.

What are some common challenges faced by a Data Ops manager, and how can they be addressed?

Data Ops Managers often encounter challenges such as coordinating across multiple teams, ensuring data quality, and managing fast-evolving data pipelines. Success in this role requires strong communication skills to align stakeholders, robust processes for monitoring data workflows, and the ability to quickly troubleshoot issues when data delivery is disrupted. Adopting automation tools and fostering a culture of continuous improvement can help Data Ops Managers maintain reliable, scalable systems while supporting organizational data needs.

What are the key skills and qualifications needed to thrive as a Data Ops manager, and why are they important?

To excel as a Data Ops Manager, you need a deep understanding of data management, analytics workflows, and process automation, often supported by a degree in computer science or a related field. Familiarity with tools like SQL, Python, cloud platforms (AWS, Azure), and orchestration systems such as Apache Airflow is typically required, along with certifications in data management or cloud services. Strong leadership, problem-solving, and communication skills help coordinate cross-functional teams and drive data initiatives. These competencies are crucial for ensuring data reliability, optimizing data pipelines, and enabling data-driven decision-making across the organization.

What is the difference between Data Ops Manager vs Data Engineer?

AspectData Ops ManagerData Engineer
Primary FocusOversees data operations, workflows, and process optimizationBuilds, constructs, and maintains data pipelines and infrastructure
Required SkillsData management, process improvement, team coordinationProgramming, database systems, ETL development
CertificationsData management, cloud certifications often preferredSQL, cloud platform certifications, programming languages
Work EnvironmentCollaborates with data teams, operations, and business unitsWorks closely with data scientists, analysts, and developers

While both roles involve working with data, the Data Ops Manager focuses on managing data workflows and operational efficiency, whereas the Data Engineer concentrates on building and maintaining data infrastructure. Understanding these differences helps in choosing the right career path or hiring the appropriate professional for your data needs.

What are the most commonly searched types of Data Ops jobs in New York?

The most popular types of Data Ops jobs in New York are:

What are popular job titles related to Data Ops Manager jobs in New York?

For Data Ops Manager jobs in New York, the most frequently searched job titles are:

What job categories do people searching Data Ops Manager jobs in New York look for?

The top searched job categories for Data Ops Manager jobs in New York are:

What cities in New York are hiring for Data Ops Manager jobs?

Cities in New York with the most Data Ops Manager job openings:

Data Ops Manager jobs near you
Infographic showing various Data Ops Manager job openings in New York as of August 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution.

Data Ops Lead

Neon Mobile, Inc

New York, NY • On-site, Remote

$150K - $190K/yr

Full-time

Re-posted 23 days ago

Job description

About Neon
Many large companies make billions each year by monetizing Americans' personal data. At Neon, we're finally cutting consumers in on the deal. Neon allows our users to make hundreds (or even thousands) of dollars per year by securely selling their anonymized data. We're backed by Lightspeed, Upper90, Upfront Ventures, and other cool investors.
About the role
Your mission is to turn Neon's raw consumer audio streams into the cleanest, most reliable training data on the market, and to build the commercial and operational engine that gets it into the hands of the world's leading AI labs.
As a Data Ops Lead, you'll own the end-to-end journey that takes raw recordings from our growing community of 500,000+ mobile users and delivers production-ready datasets to frontier labs. In practice, that means three things above all:
  • Structuring and managing the data deals that turn our recordings into revenue
  • Holding every dataset to a quality bar that keeps buyers coming back
  • Standing up human transcription, annotation and other operations, largely overseas, that make it all possible

You'll work directly with our CEO on commercial priorities and help shape each deal, interface with buyer-side engineering and research teams at frontier labs to translate their exact specifications into deliverable dataset plans, and partner with internal engineering and external vendors to make sure the pipeline supports what we've sold. This is a foundational role: the datasets and processes you build are the product we sell.
We're a small, early-stage team moving fast. Expect roughly 60 hours per week, with occasional weekend work around launches and deadlines. We're upfront about this because we'd rather find people who are energized by that pace than surprise anyone after they join.
You have...
  • Authorization to work in the US.
  • 5+ years of experience building and scaling data pipelines for AI/ML applications, with significant time spent on audio, speech, or multimodal data.
  • A track record of structuring and delivering against data or dataset agreements with external partners: taking their requirements, turning them into clear specifications, and owning delivery end to end.
  • Experience building and managing overseas or outsourced teams for data tagging, annotation, and QA, with a track record of maintaining quality and throughput across time zones.
  • Deep ownership of data quality: designing QA processes, defining acceptance criteria, and catching problems before a customer ever sees them.
  • Enough technical fluency to be credible on both sides of a deal. You understand digital audio fundamentals (sample rates, VAD, multichannel formats), can reason about how pipelines are built, and know what "good" looks like, even if you're not writing every line of code yourself.
  • A "Founder's Mentality." You're comfortable building from zero and making high-stakes calls with incomplete information.

Bonus points
  • A background working with audio data in some capacity.
  • Direct experience with training data for TTS, ASR, speaker ID, or full-duplex conversational models.
  • Familiarity with the modern audio stack (Librosa, FFmpeg, SoX, torchaudio) and cloud data infrastructure (S3, Redshift, BigQuery, or equivalent).
  • An understanding of how high-quality, speaker-separated audio gets captured (for example, via WebRTC-based recording tools).
  • Experience with active learning loops, human-in-the-loop QA systems, or corpus stratification for balanced dataset design.
  • Prior experience leading a data or infrastructure team, including hiring and mentoring engineers.

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