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Data Extraction Jobs in Texas (NOW HIRING)

... data extraction and manipulation. 10 Required Experience collaborating with end-users and performance analysts or IT internal leaders to create and validate reports, dashboards, and data ...

Data Engineer

Plano, TX · On-site

$100 - $140/hr

Advanced knowledge of Extract/Transform/Load (ETL) and/or Extract/Load/Transform (ELT) tools, including both batch and real-time data transmission applications such as SSIS, Informatica, Kafka, Spark ...

Posted today

Responsibilities : • Support the build-out and maintenance of ETL/ELT pipelines that collect, transform, and load financial data from multiple sources into our internal platform, ensuring accuracy ...

Data Engineer

Dallas, TX · On-site

$110 - $170/hr

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

GCP Data Engineer

Austin, TX

$113K - $136K/yr

Experience with ETL processes and data pipeline design. * Design, build, and maintain scalable data pipelines using Google Cloud Platform tools such as BigQuery, Cloud Storage, Dataflow (Apache Beam ...

Data Scientist

Plano, TX · On-site

$62 - $67/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 ...

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 ...

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 ...

Senior Data Analyst

Plano, TX · On-site

$82K - $104K/yr

Responsibilities : • Extract, clean, and analyze large datasets from financial systems using advanced SQL queries. • Interpret financial data to identify trends, anomalies, and opportunities for ...

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 ...

... 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 ...

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 management, 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, and understanding data privacy and security is also beneficial.

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 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Data Conversion Specialist - Austin, TX (Hybrid/Remote)

My3Tech

Austin, TX • On-site

$70 - $90/hr

Contractor

Retirement

Posted 12 days ago


Job description

AI Data Conversion Specialist

Austin, TX (Hybrid/Remote)

Long-term Contract

Required Skills and Experience:

Years

Skills / Experience

4+

Data conversion development for large-scale pension administration system modernization programs; source-to-target mapping, ETL execution, exception handling, and validation across multi-billion-record legacy data sets.

4+

SSIS package development and BIML scripting for automated, repeatable data extraction, transformation, and load processes across legacy pension and structured relational data environments.

4+

SQL Server and T-SQL development including complex stored procedures, views, indexing strategies, query optimization, and execution plan analysis to support high-volume ETL and reconciliation workflows.

3+

C# and .NET development for data conversion automation scripts, SSIS custom components, and backend data processing logic within a structured SDLC environment.

3+

Legacy system data migration experience including source environments; multi-environment extract and load processes; participation in mock runs, UAT cycles, and production cutover activities.

2+

Data reconciliation including record count validation, key field comparison, exception reporting, authorization and exclusion logic, and validation within a large-scale pension or benefits modernization platform.

1+

Large-scale public pension administration system modernization data conversion experience.

1

Database Administrator experience.

Preferred Skills and Experience:

Years

Skills / Experience

3+

Azure Data Factory, PySpark, or Apache Airflow pipeline development for ELT/ETL orchestration, incremental loading strategies, and data quality validation in cloud or hybrid data environments.

2+

Power BI or SSRS dashboard and report development including ETL job completion tracking, exception rate reporting, and data quality KPI visualization for program leadership and QA teams.

2+

Cloud data warehouse development using dbt Core for staging, intermediate, and reporting layer transformations with incremental load strategies (SnowPro Core or Microsoft Fabric certification a plus).

2+

Defect triage and root cause analysis using SQL scripts and SSIS debugging techniques; cross-functional collaboration with QA, functional testers, and business analysts during mock loads and UAT resolution cycles.