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Data Processor Jobs in Dallas, TX (NOW HIRING)

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

We are seeking a skilled PySpark Data Engineer to join our team and drive the development of robust data processing and transformation solutions within our data platform. You will be responsible for ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

New

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

New

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

New

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

New

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries. * Experience working with ...

Showing results 41-60

Data Processor information

See Dallas, TX salary details

$12

$20

$34

How much do data processor jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for data processor in Dallas, TX is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $15.96 and $22.12 per hour, depending on experience, location, and employer.

What is a data processor?

A data processor transfers, organizes, and processes personal data for a company. It is typically an entry-level job that serves as a starting point for a career as a data controller. As a data processor, your duties involve processing incoming documents, transferring analog documents into digital data, verifying the information in all documents, updating document formats, and creating detailed reports on company data use and management. Qualifications for this career include excellent computer skills and a bachelor’s degree in computer science or data management.

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

To thrive as a Data Processor, you need strong attention to detail, accuracy in data entry, and a high school diploma or equivalent. Familiarity with spreadsheet software (such as Microsoft Excel), database management systems, and sometimes data processing software is typically required. Excellent organizational skills, the ability to follow procedures, and effective time management make someone stand out in this role. These skills ensure data integrity, minimize errors, and support efficient information management within an organization.

What are some common challenges faced by data processors and how can they be addressed?

Data Processors often encounter challenges such as managing large volumes of data accurately and efficiently, dealing with inconsistent or incomplete data, and ensuring data privacy and compliance. To address these, it's important to develop strong attention to detail, become proficient with data processing software, and stay updated on relevant data protection regulations. Collaborating closely with data analysts and IT teams can also help resolve data issues and improve workflow efficiency.

What is the difference between Data Processor vs Data Entry Clerk?

AspectData ProcessorData Entry Clerk
Required CredentialsHigh school diploma; some roles may require basic certificationsHigh school diploma; no specialized certifications typically needed
Work EnvironmentOffice settings, data centers, or remote workOffice environments, often in administrative settings
Employer & Industry UsageBusinesses, government agencies, financial institutionsCorporations, healthcare, retail, administrative offices
Common Search & ComparisonOften compared for data handling and processing tasksCompared for data input and administrative support roles

While both roles involve handling data, Data Processors typically perform more complex data management and validation tasks, often requiring some technical skills. Data Entry Clerks focus on inputting data accurately and efficiently. Understanding these differences helps in choosing the right role based on skills and career goals.

How much does a data processor earn?

The average salary for a data processor in the United States ranges from $30,000 to $50,000 per year, depending on experience, location, and industry. Entry-level positions may start lower, while experienced data processors with specialized skills or certifications can earn higher wages. Salaries are often complemented by benefits such as health insurance and paid time off.

What do you do as a data processor?

A data processor collects, organizes, and manages data to ensure accuracy and accessibility. They often use software tools like spreadsheets or databases and may perform tasks such as data entry, validation, and updating to support business operations.

What cities near Dallas, TX are hiring for Data Processor jobs?

Cities near Dallas, TX with the most Data Processor job openings:

Infographic showing various Data Processor job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $41,717 per year, or $20.1 per hour.

$140/hr

Full-time

Medical, Life, Retirement, PTO

Re-posted 29 days ago


Job description

CompanyFederal Reserve Bank of St. LouisThe Federal Reserve Bank of St. Louis is seeking a Research Platform Architect to lead the technical vision and long-term architecture of its global economic research platforms such as FRED and FRASER. These platforms provide access to hundreds of thousands of economic time-series datasets, historical archives, and research publications used by millions of economists, policymakers, researchers, students, and developers worldwide.

The Data Architectwill lead the design and modernization of the data architecture that powers the economic data platforms of St. Louis based Research applications such as FRED. These platforms manage massive collections of economic time-series data, historical revisions, digitized archival documents, and research publications.

This role focuses on designing scalable data platforms, data models, and data governance frameworksto support long-term growth, advanced analytics, and global access to economic data. It will leverage in-depth knowledge of modern data technologies, industry frameworks, data security best practices and emerging innovations in AI/ML and data science to accelerate value, delivery and outcomes for the business.

The Data Architect will partner closely with the Application/Enterprise Architectto ensure seamless integration between data platforms and application services.

Key Responsibilities

  • Define and evolve the target data architecturesupporting economic data systems.
  • Design scalable storage architectures capable of supporting billions of time-series observations and historical revisions.
  • Develop metadata schemas supporting dataset discoverability, lineage, and governance.
  • Standardize dataset structures and metadata across multiple platforms.
  • Implement scalable data processing frameworks capable of supporting growing dataset volumes.
  • Improve indexing and metadata strategies that support dataset search and discovery.
  • Enable advanced analytical capabilities for researchers and developers.
  • Partner with the Application Architect to optimize data access patterns for APIs and applications.

Required Qualifications

  • 7+ years of experience in data architecture, data engineering or database design and large-scale enterprise cloud data implementations in complex, highly regulated environments. Deep understanding of modern data technology stacks, cloud data platforms (AWS preferred), and enterprise software solutions.
  • Demonstrated experience designing, architecting and supporting external / public-facing applications with a strong emphasis on scalability, security, availability and performance for external customer-facing platforms. Demonstrated knowledge of and leading adoption of industry best practices in the areas of DataOps and modern data stack tools, data governance, SQL and other query tools and knowledge of data privacy regulations. Industry-related certifications in one or more of the above areas are desired.
  • Demonstrated experience in cloud data architecture skills including designing, architecting and delivering modern cloud data platforms to ingest, process, store and expose data across the enterprise. Expert knowledge of data modeling techniques and tools, data lifecycle management and integration patterns to ensure that data flows are consistent, reliable and reusable across services and solutions. Experience with data storage technologies, partitioning strategies, caching, data access patterns, and robust security strategies enforcing privacy and regulatory requirements including designing standardized approaches for data classification, access control, encryption, retention and auditability. Knowledge of data warehousing concepts and tools, big data technologies, machine learning and AI data requirements.
  • Outstanding communication and collaboration skills, including translating technical topics and risks into business teams. Ability to personalize communication to audience from technologists to executive leadership.
  • Extensive, in-depth experience implementing highly complex technology projects in a cross-functional matrix environment with demonstrated ability to drive consensus and deliver results. Examples of leading through influence and successfully resolving conflicting priorities are required.

Preferred Qualifications

  • Experience working with time-series data platforms or analytical datasets.
  • Experience with distributed query engines and large-scale data processing systems.
  • Experience with data catalog and metadata management platforms.
  • Familiarity with economic datasets or research data environments.
  • Experience supporting public data access or research-oriented platforms.

Total Rewards

Bring your passion and expertise, and we'll provide the opportunities that will challenge you and propel your growth-along with a wide range of benefits and perks that support your health, wealth, and life.

Salary: $140-170k

In addition to competitive compensation, we offer a comprehensive benefits package that all brought together in a flexible work environment where you can truly find balance:

  • Generous paid time off
  • Tuition & Training assistance/reimbursement
  • 401(k) match & Annuity/Pension fund
  • Top-notch health care benefits
  • Child and family care leave
  • Professional development opportunities
  • And more...

At the Federal Reserve Bank of St. Louis, we are committed to a strong and resilient economy for all. We prioritize inclusion and strive to be a workplace where all employees can thrive. Learn more about Bank's culture

The Federal Reserve Bank of St Louis is an Equal Opportunity Employer.

Full Time / Part TimeFull timeRegular / TemporaryRegularJob Exempt (Yes / No)YesJob CategoryInformation Technology Family GroupWork ShiftFirst (United States of America)

The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.

Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.

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