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Data Extraction Jobs in Texas (NOW HIRING)

Data Scientist

Plano, TX · On-site

$110 - $150/hr

Experience with SQL for data extraction and manipulation * Familiarity with version control (Git) and CI/CD for model deployment * Comfort working in cloud ML environments (AWS SageMaker, Azure ML ...

Sr. Data Engineer

Addison, TX · Hybrid

$102K - $139K/yr

Design and optimize complex ETL/ELT data pipelines using Azure Data Factory, other Azure services and python, ensuring high reliability and performance. Orchestrate pipelines that leverage AI/LLMs ...

Sr. Data Engineer

Addison, TX · On-site

$102K - $139K/yr

... complex ETL/ELT data pipelines using Azure Data Factory, other Azure services and python, ensuring high reliability and performance. • Orchestrate pipelines that leverage AI/LLMs for data ...

... data extraction, transformation, and loading. * Analyze business requirements and translate them into technical ETL solutions. * Develop and optimize complex SQL queries, stored procedures, and ...

Sr. Data Engineer

Addison, TX · Hybrid

$102K - $139K/yr

... complex ETL/ELT data pipelines using Azure Data Factory, other Azure services and python, ensuring high reliability and performance. • Orchestrate pipelines that leverage AI/LLMs for data ...

Data Engineer

Plano, TX · On-site

$80K - $100K/yr

DataStage, SQL, Python, Snowflake, DBT Roles & Responsibilities * 1-3 years of experience in ETL/ELT and Data Warehousing principles utilizing Datastage and/or python and snowflake and dbt * Organize ...

... for data extraction, reporting, and analytics solutions. 3. Design, develop, test, optimize, and maintain Cerner Command Language (CCL) scripts within Cerner Millennium environments. 4. Perform ...

Data Analyst

Austin, TX · On-site

$40 - $50/hr

Write complex SQL queries to extract, transform, and analyze data from multiple sources. * Develop Python-based analytical solutions for data processing and automation. * Evaluate data quality and ...

Write, optimize, and maintain complex SQL queries to extract, manipulate, and analyze data from various database sources. * Ensure the reliability, consistency, and accuracy of all data outputs by ...

Data Engineer

Grand Prairie, TX · On-site

$109K - $131K/yr

... real-time data extraction. * Applied experience with OEE, Six Sigma, SPC, and lean methodologies to drive measurable gains in yield, uptime, and efficiency. Disclaimer: Nagarro is an equal ...

Data Engineer

Sherman, TX · On-site

$102K - $122K/yr

Developing and maintaining server-side Extract Transform Load (ETL) data pipelines and custom databases. * Formulating and coding algorithms in support of data transformation. * Troubleshooting ...

Showing results 41-60

Data Extraction information

What is a data extraction?

A Data Extraction job involves collecting and retrieving data from various sources, such as databases, documents, websites, and APIs. This data is then transformed, cleaned, and structured for analysis or storage. Professionals in this role use tools like SQL, Python, or web scraping technologies to automate the process. Data extraction is essential for businesses to gain insights, make data-driven decisions, and streamline operations.

What are the typical daily responsibilities for someone working in data extraction?

Professionals in Data Extraction typically spend their days gathering data from a variety of sources—such as databases, websites, or documents—using specialized tools or scripts. They are responsible for cleaning, formatting, and validating this data to ensure accuracy and consistency before delivering it to analysts or other stakeholders. Collaborating with data analysts, IT teams, and business units is common to clarify data requirements and resolve any discrepancies. Most roles involve a mix of independent technical work and teamwork, with some positions requiring regular reporting or documentation of data extraction processes.

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

To excel in Data Extraction, candidates should have strong analytical skills, attention to detail, and a background in data management or computer science. Experience with extraction tools and programming languages such as SQL, Python, R, or ETL platforms, as well as familiarity with data governance standards, is often required. Strong organizational, problem-solving, and communication skills help professionals handle complex datasets and collaborate effectively across teams. These competencies ensure accurate, efficient data retrieval and support informed business decisions.

How to become a data extraction?

To become a data extraction specialist, develop skills in data analysis, programming languages like Python or SQL, and familiarity with data extraction tools such as web scrapers or ETL software. Gaining experience through relevant projects or certifications can improve job prospects in this field.

What are the most commonly searched types of Data Extraction jobs in Texas?

The most popular types of Data Extraction jobs in Texas are:

What are popular job titles related to Data Extraction jobs in Texas?

For Data Extraction jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Data Extraction jobs in Texas look for?

The top searched job categories for Data Extraction jobs in Texas are:

What cities in Texas are hiring for Data Extraction jobs?

Cities in Texas with the most Data Extraction job openings:

Infographic showing various Data Extraction job openings in Texas as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% In-person job distribution.

Data Scientist

CCS INC

Plano, TX • On-site

$110 - $150/hr

Other

Medical, Dental, Vision

Posted 6 days ago


Job description

Benefits

  • Dental insurance

  • Health insurance

  • Vision insurance


About the Role

We're looking for a Data Scientist who can turn complex data into clear, actionable insights and help us move models from idea to production.


Qualifications

  • Master's degree (or higher) in a quantitative field, or equivalent professional experience

  • Strong Python skills, with hands‑on experience in libraries like scikit‑learn, statsmodels, or PyTorch

  • Solid grounding in statistical and ML methods (regression, time series, predictive modeling, tree‑based methods, neural networks, etc.)

  • Experience with SQL for data extraction and manipulation

  • Familiarity with version control (Git) and CI/CD for model deployment

  • Comfort working in cloud ML environments (AWS SageMaker, Azure ML, or similar)

  • A track record of applying data science to real business problems, not just academic settings

  • Strong communication skills — able to translate technical findings for non‑technical audiences

  • Experience modernizing legacy data infrastructure is plus

  • History of driving cross‑team initiatives without direct authority is preferred


Responsibilities

  • Partner with business stakeholders to identify high‑impact questions and translate them into data‑driven answers

  • Clean, prepare, and analyze data from multiple sources

  • Build and deploy predictive/prescriptive models that solve real business problems

  • Communicate findings through clear visualizations and reporting
  • Ship models to production within our cloud infrastructure

  • Contribute to planning and prioritization of data initiatives

  • Keep current with new tools and techniques in the field

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