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Data Hub Jobs (NOW HIRING)

RXinsider LTD.

Job Summary Bureau Veritas is seeking an experienced Regional AI & Data Hub Technical Lead to provide technical leadership for one of our regional AI delivery hubs. This role is responsible for ...

Motorola

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

Motorola

Product Owner (Product Data Hub)

Tennessee, IL · Hybrid

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

Motorola

Product Owner (Product Data Hub)

Florida, NY · Hybrid

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

Motorola

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

Motorola

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

RXinsider LTD.

Job Summary Bureau Veritas is seeking a strategic and people-focused Regional AI & Data Hub Manager to lead one of our regional AI delivery hubs. In this role, you will partner with business leaders ...

Motorola

Product Owner (Product Data Hub)

New York, NY · Hybrid

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

Motorola

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

Motorola

Oracle Product Data Hub (PDH) and Informatica MDM. As we approach the rollout of Phase 1, we are seeking a dynamic, data-savvy Product Owner to champion this platform from the business side. In this ...

Bureau Veritas

Texas Job Summary Bureau Veritas is seeking an experienced Regional AI & Data Hub Technical Lead to provide technical leadership for one of our regional AI delivery hubs. This role is responsible for ...

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Data Hub information

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How much do data hub jobs pay per year?

As of Sep 13, 2026, the average yearly pay for data hub in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a data hub?

A Data Hub is a centralized platform or system that collects, integrates, manages, and distributes data from various sources across an organization. It acts as a single point of access for data users, making it easier to share, govern, and consume data efficiently. Data Hubs are commonly used to break down silos, ensure data consistency, and support analytics, reporting, and business intelligence initiatives. They differ from data warehouses or data lakes by focusing on integration and accessibility rather than just storage or analytics.

What are some common challenges faced by professionals working in data hub roles, and how are they typically addressed?

Professionals in Data Hub roles often encounter challenges related to integrating data from multiple sources, ensuring data quality, and maintaining data security. These challenges are typically addressed by implementing standardized data governance practices, using advanced ETL (Extract, Transform, Load) tools, and collaborating closely with IT, data engineering, and business teams. Regular data audits and adopting robust access controls also help ensure that data remains accurate and secure. Staying up to date with evolving technologies and best practices is key to overcoming these hurdles.

What are the key skills and qualifications needed to thrive as a data hub specialist, and why are they important?

To thrive as a Data Hub Specialist, you need a strong foundation in data management, integration techniques, and database querying, often supported by a degree in computer science or information systems. Familiarity with ETL (Extract, Transform, Load) tools, data warehousing platforms, and cloud technologies like Azure or AWS is typically required. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with stakeholders to ensure data accuracy and accessibility. These skills and qualities are vital for maintaining reliable data flows and supporting informed business decisions across the organization.

What is the difference between Data Hub vs Data Analyst?

AspectData HubData Analyst
Required CredentialsTypically requires data management certifications, knowledge of data integration toolsOften requires a degree in statistics, data science, or related fields
Work EnvironmentWorks with data infrastructure, integration, and storage systemsFocuses on analyzing data, creating reports, and providing insights
Employer & Industry UsageUsed in organizations managing large data ecosystems, tech, finance, healthcareCommon in business, marketing, finance, and consulting sectors

While both roles involve working with data, a Data Hub primarily manages data infrastructure and integration, ensuring data flows smoothly across systems. A Data Analyst focuses on interpreting data, generating reports, and providing insights to support decision-making. Understanding these differences helps organizations assign the right roles for their data needs.

What do data hubs do?

A data hub is a centralized platform that consolidates, integrates, and manages data from multiple sources to ensure consistent and accessible information across an organization. Data hub specialists often work with data integration tools, databases, and data governance practices to improve data quality and support analytics efforts.
More about Data Hub jobs

What job categories do people searching Data Hub jobs look for?

The top searched job categories for Data Hub jobs are:

Data Hub jobs near you
Infographic showing various Data Hub job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Engineer- Enterprise Data Hub (Insurance Domain, AWS)

New York, NY • On-site

Accord Technologies Inc.
IT Services • 51 - 200 employees
Learn more about Accord Technologies Inc.external

Contractor

Re-posted 11 days ago

Job description

Data Engineer – Enterprise Data Hub (Insurance Domain, AWS)
Location: New York, NY
Duration: long term
Position type: W2 contract 
Position type:

We are looking for Data Engineer supporting the development and maintenance of Enterprise Data Hub within the insurance domain. The ideal candidate will have strong experience in AWS cloud services, data pipeline development, and insurance data models. This role will play a key part in enabling data-driven decision-making across the organization. The successful candidate will collaborate closely with data architects, enterprise architects, infrastructure, and other cross-functional teams to build data pipelines that are scalable and aligned to best practices for data management, change management, integration, and analysis This is an exciting opportunity to work on cutting-edge technologies, solve complex challenges, and drive impactful insights that fuel our company's success. The role reports to the Enterprise Data Hub Product Lead.

This role is ideal for a proactive and detail-oriented professional who is passionate about development, governance and controls. If you thrive in a dynamic environment and are committed to maintaining high standards of IT control, this position offers a rewarding opportunity to make a significant impact.

Your skills and abilities should include:

  • 10+ years of experience in data engineering or related roles, in the insurance industry.(Re-insurance)
  • Strong hands-on experience with AWS data services (e.g., Glue, Redshift, S3, Athena, Lambda, EMR).
  • Proficiency in SQL, Python, and data modelling.
  • Experience with ETL tools and frameworks.
  • Familiarity with insurance data domains (e.g., claims, policy, billing).
  • Understanding of data governance, lineage, and compliance (e.g., HIPAA, GDPR).
  • Experience with CI/CD and version control tools (e.g., Git, CodePipeline).
  • AWS or Solutions Architect certifications are not required but preferred.
  • Experience with data lakes and lakehouse architectures is a strong plus.
  • Exposure to BI tools (e.g., Power BI, Tableau, QuickSight) is preferred.
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field is a strong plus.
  • Excellent organizational, communication, and interpersonal skills. 
  • Ability to work individually with limited oversight.
  • Ability to prioritize, multi-task, and maintain flexibility in a fast-paced, changing environment.
  • Demonstrated ability to influence and work effectively within a global organization with employees at all levels.
  • Motivated, team-oriented, with strong problem-solving and project management skills.

Key Responsibilities

  • Design, build, and maintain scalable data pipelines and ETL processes for the Enterprise Data Hub.
  • Implement data ingestion, transformation, and storage solutions using AWS services (e.g., Glue, Redshift, S3, Athena, Lambda, EMR).
  • Work with structured and unstructured data from variousinsurance systems (e.g., policy, claims, underwriting).
  • Collaborate with data architects, analysts, and business stakeholders to understand data requirements.
  • Collaborate with enterprise architects to understand integration design patterns. 
  • Collaborate with infrastructure to align to best practices for code deployments and change management.
  • Ensure data quality, integrity, and governance across the data lifecycle.
  • Optimize data workflows for performance, scalability, and cost-efficiency.
  • Support data cataloguing and metadata management initiatives.
  • Implement security and compliance best practices for sensitive insurance data