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Data Extraction Analyst Jobs in Texas (NOW HIRING)

Amazon

Business Analyst II - AMZ9442618

Irving, TX · On-site

$74K - $130K/yr

Analyze forecast and metrics data. Automate reports for promotional and project launch campaigns. Utilize database technologies, including SQL, ETL, and Oracle to design, develop, and evaluate highly ...

City of Georgetown, TX

IT Architect - Data Architect

Loop, TX · On-site

$62 - $79.75/hr

Data/Analytics Architect: Models and designs warehouses/lakes, builds pipelines (ETL/ELT), andenables analytics/BI platforms and self-service reporting. Application/Integration Architect: Produces ...

Amazon

Business Analyst III - AMZ9084949

Austin, TX · On-site

$118K - $160K/yr

... data analyses, model development, validation, and implementation. Utilize advanced database technologies, including SQL, ETL, and Oracle to develop and evaluate highly innovative business ...

Real Soft, Inc.

Data Scientist

San Antonio, TX · On-site

Strong experience with Python (data manipulation, scripting, analytics) * Experience working with SQL databases (Postgres preferred) * Experience with data extraction, transformation, and preparation ...

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All JobsData Extraction Analyst JobsData Extraction Analyst Jobs in Texas

Data Extraction Analyst information

See Texas salary details

$31.7K

$77K

$126.7K

How much do data extraction analyst jobs pay per year?

As of Jun 15, 2026, the average yearly pay for data extraction analyst in Texas is $76,992.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $90,400.00 per year, depending on experience, location, and employer.

What is the difference between Data Extraction Analyst vs Data Analyst?

AspectData Extraction AnalystData Analyst
Primary FocusExtracting, cleaning, and preparing data from various sourcesAnalyzing data to identify trends and support decision-making
Skills & ToolsSQL, data scraping, ETL tools, data managementExcel, statistical analysis, visualization tools, SQL
Work EnvironmentData warehouses, databases, ETL pipelinesReporting platforms, dashboards, business intelligence tools
Common IndustriesIT, finance, marketing, e-commerceFinance, healthcare, marketing, consulting

While both roles involve working with data, Data Extraction Analysts focus on retrieving and preparing data for analysis, whereas Data Analysts interpret and analyze data to generate insights. Understanding these differences helps in choosing the right career path or job search focus.

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

To thrive as a Data Extraction Analyst, strong analytical skills, attention to detail, and proficiency in data management are essential, often supported by a degree in computer science, information systems, or a related field. Familiarity with ETL (Extract, Transform, Load) tools, SQL databases, and data visualization software is typically required, and certifications in data analytics or database management can be advantageous. Excellent problem-solving abilities, communication skills, and adaptability help analysts effectively interpret data requirements and collaborate with stakeholders. These skills ensure accurate data extraction, support informed decision-making, and maintain data integrity in complex organizational environments.

What skills are needed for data extraction?

Data Extraction Analysts need strong analytical skills, attention to detail, and proficiency with data management tools such as SQL, Excel, or specialized extraction software. Knowledge of programming languages like Python or R and understanding of data structures and databases are also important for efficient data retrieval and processing.

Is 40 too late for data science?

For a Data Extraction Analyst or similar data-related roles, age is generally not a barrier if you have relevant skills such as data analysis, SQL, or Python. Many professionals transition into data science or analytics later in their careers, and continuous learning through certifications or courses can enhance employability regardless of age.

Is AI replacing data analysts?

AI is automating certain tasks within data analysis, such as data cleaning and basic reporting, but it does not replace the need for data analysts. Data analysts are essential for interpreting complex data, making strategic decisions, and developing insights that require human judgment and domain expertise. The role continues to evolve, emphasizing skills in data visualization, programming, and understanding AI tools.

What is a Data Extraction Analyst?

A Data Extraction Analyst is a professional responsible for collecting, processing, and interpreting data from various sources, such as databases, documents, and websites. They use specialized tools and software to extract relevant data, ensuring its accuracy and integrity. Their work supports business decisions, reporting, and analytics by making data accessible and usable for organizations. Data Extraction Analysts often collaborate with IT, data science, and business teams to streamline data workflows and comply with data privacy regulations.

What jobs will boom in 2026?

Data Extraction Analysts are expected to see increased demand as organizations rely more on data-driven decision-making. Skills in data mining, SQL, and automation tools will be valuable, and roles may expand in industries like finance, healthcare, and technology. Continuous learning and certifications in data management can enhance job prospects in this field.

What are the most common challenges Data Extraction Analysts face when working with unstructured data sources?

Data Extraction Analysts often encounter challenges when dealing with unstructured data, such as inconsistent formats, incomplete records, and noisy or irrelevant information. Extracting reliable data from sources like scanned documents, emails, or social media posts requires advanced tools and techniques, including optical character recognition (OCR) and natural language processing (NLP). Overcoming these challenges typically involves close collaboration with data engineers and subject matter experts, as well as continuous refinement of extraction processes to maintain data quality and accuracy.
What are popular job titles related to Data Extraction Analyst jobs in Texas? For Data Extraction Analyst jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Extraction Analyst jobs in Texas look for? The top searched job categories for Data Extraction Analyst jobs in Texas are:
Data Extraction Analyst jobs near you
Infographic showing various Data Extraction Analyst job openings in Texas as of June 2026, with employment types broken down into 3% Locum Tenens, 14% As Needed, 21% Full Time, 10% Part Time, and 52% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $76,992 per year, or $37 per hour.
Business Analyst - Finance & Data Management (Hybrid)

Business Analyst - Finance & Data Management (Hybrid)

The Dignify Solutions, LLC

Frisco, TX • Hybrid

Other

Posted 27 days ago

Job description

Job Title

Location: Frisco, TX or Seattle, WA

Job Description

Gather, analyze, and document business requirements related to finance and data management.

Work closely with stakeholders to translate business needs into technical specifications.

Create data mapping documents, testing framework for integration testing.

Utilize SQL for data extraction, transformation, and analysis.

Apply ETL/DW concepts to support data warehousing and reporting initiatives.

Collaborate with development teams in an Agile environment to ensure timely delivery of solutions.

Conduct financial analysis and generate reports to support decision-making.

Act as a liaison between business and technical teams to ensure seamless communication.

Support testing and validation of implemented solutions.

Required Skills & Qualifications

Educational Background: Bachelor's or master's degree in finance, business, economics, computer science, or related fields.

Technical Skills: Strong knowledge of SQL and ETL/DW concepts.

Industry Experience: Finance/Telecom industry experience is a plus.

Tools & Platforms: Familiarity with Fynapse is desirable.

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About Dignify Solutions

Sourced by ZipRecruiter

The Dignify Best Serves To Its Clients By Adhering To And Executing Superior Processes. The company is dedicated to operational excellence as part of a client-centric mindset that assures consistent execution. The Dignify has developed and refined every step in the full lifecycle staffing fulfillment and consultant management practice

Industry

It services

Company size

51 - 200 Employees

Headquarters location

San Francisco, CA, US

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