1

Data Processing Jobs in Spring, TX (NOW HIRING)

Data Engineer

Houston, TX

$109K - $131K/yr

S3 never asks for money during its onboarding process." Job Title: Data Engineer Location: Houston, TX Contract Length: 12+ Months Job ref# 247245 Seeking a Senior Data Engineer to support Enterprise ...

Architect and optimize ETL/ELT pipelines for batch and real-time processing. * Collaborate with business stakeholders and technical teams to define data strategies and solutions. * Ensure data ...

Python, NoSQL, SQL, R, and competent in source code management Build processes supporting data transformation, data structures, metadata, dependency, and workload management Create data validation ...

Azure Data Engineer (Houston, TX)

Houston, TX · On-site

$109K - $131K/yr

Automate data processing of data from multiple data sources * Develop, deploy and version control code for data consumption, reuse for APIs * Employ machine learning techniques to create and sustain ...

Senior Data Analyst

Houston, TX · On-site

$50 - $53/hr

Document report specifications, data models, and development processes to support maintainability and knowledge sharing. * Develop and maintain automated reporting workflows using Power Platform ...

New

Proficiency in Python and data processing libraries such as Pandas, NumPy, or PySpark. * Strong understanding of data governance, metadata management, data quality, and compliance best practices.

Experience using AIbased document extraction tools and data processing technologies. * Familiarity with MineralSoft and EnergyLink platforms (preferred). * Strong understanding of data mapping ...

Showing results 21-40

Data Processing information

See Spring, TX salary details

$10

$18

$31

How much do data processing jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for data processing in Spring, TX is $18.03, according to ZipRecruiter salary data. Most workers in this role earn between $14.33 and $19.90 per hour, depending on experience, location, and employer.

What is data processing?

A Data Processing job involves collecting, organizing, and managing data to ensure accuracy and accessibility. Professionals in this role use software tools to input, clean, analyze, and process data for businesses or organizations. They may also generate reports and automate workflows to streamline data handling. Strong attention to detail and proficiency in data management tools are essential for success in this field.

What are the typical daily responsibilities of someone working in data processing?

A typical day for a Data Processing professional involves entering, validating, and updating records in databases or spreadsheets to ensure data integrity. You may also be responsible for generating reports, cleaning large data sets, and identifying discrepancies or errors for correction. Collaboration with team members or departments is common to clarify data requirements and resolve issues. Staying organized and attentive to detail is essential because the quality of processed data can impact decision-making across the organization.

What are the key skills and qualifications needed to thrive in data processing, and why are they important?

To thrive in Data Processing, you need strong analytical abilities, attention to detail, and proficiency with spreadsheets and database management, often supported by an associate's degree or relevant experience. Familiarity with tools like Microsoft Excel, SQL, or data entry software, as well as certifications such as Certified Data Processor (CDP), are frequently expected. Strong organizational skills, time management, and the ability to troubleshoot problems efficiently are valued soft skills. These competencies are crucial for ensuring data accuracy, meeting deadlines, and supporting smooth information operations within an organization.

What do you do as a data processing?

A data processing professional collects, organizes, and analyzes data to ensure accuracy and usability. They use tools like spreadsheets, databases, and data management software to clean, transform, and prepare data for reporting or decision-making. Attention to detail and knowledge of data handling techniques are essential in this role.

What is a data processing job role?

A data processing job involves collecting, organizing, and converting raw data into a usable format for analysis or reporting. It often requires skills in data management tools, attention to detail, and knowledge of data formats and software such as Excel, SQL, or specialized processing programs.

What are popular job titles related to Data Processing jobs in Spring, TX?

For Data Processing jobs in Spring, TX, the most frequently searched job titles are:

What job categories do people searching Data Processing jobs in Spring, TX look for?

The top searched job categories for Data Processing jobs in Spring, TX are:

What cities near Spring, TX are hiring for Data Processing jobs?

Cities near Spring, TX with the most Data Processing job openings:

Infographic showing various Data Processing job openings in Spring, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $37,512 per year, or $18 per hour.

$109K - $131K/yr

Full-time

Re-posted 21 days ago


Job description

Job Description STRATEGIC STAFFING SOLUTIONS HAS AN OPENING. This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position.

Visa Sponsorship is Available. The details are below. "Beware of scams.

S3 never asks for money during its onboarding process." Job Title: Data Engineer Location: Houston, TX Contract Length: 12+ Months Job ref# 247245 Seeking a Senior Data Engineer to support Enterprise AI initiatives within the Shale & Tight business. This is a senior, hands-on engineering role responsible for designing, developing, and optimizing scalable cloud-based data platforms and pipelines that enable AI, analytics, and machine learning solutions. The ideal candidate can work independently, solve complex technical problems, provide technical leadership, mentor engineers, and partner with Software Engineers, AI Engineers, Data Scientists, and business stakeholders to deliver enterprise-scale data solutions

Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent experience) 10+ years of Data Engineering experience Expert-level Python and SQL development Experience designing and building scalable ETL/ELT data pipelines Strong experience with AWS, Azure, or GCP Experience with distributed data processing technologies such as Spark or Databricks Experience with data modeling, data architecture, and data integration Experience with orchestration tools such as Airflow, Azure Data Factory (ADF), or AWS Glue Experience working with both structured and unstructured data Experience with CI/CD, Git, and DevOps best practices Proven experience designing enterprise-scale data platforms and pipelines Experience building data solutions supporting analytics, AI, or machine learning workloads Strong troubleshooting and root cause analysis skills Demonstrated experience providing technical leadership and mentoring Data Engineers Excellent verbal and written communication skills Ability to work independently, prioritize competing initiatives, and thrive in ambiguous environments Key Responsibilities Design, develop, and optimize scalable cloud-based data pipelines and platforms Translate complex business requirements into technical solutions Partner with Software Engineers, AI Engineers, Data Scientists, and business stakeholders to deliver enterprise AI data solutions Lead the design and implementation of scalable, secure, and maintainable data architectures Improve existing data infrastructure through automation and engineering best practices Ensure data quality, governance, reliability, and platform performance Troubleshoot production issues and perform root cause analysis Mentor junior and mid-level Data Engineers while providing technical leadership Drive engineering standards, documentation, and code quality