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Data Extraction Jobs in Colorado (NOW HIRING)

Apetan Consulting llc

Business (Data) Analyst

Denver, CO · On-site

$80 - $150/hr

SQL, SNOWFLAKE, DATABRICKS, AWS, REDSHIFT, DATA WAREHOUSE, ETL * Experience: 7 + years * Develop Data Solutions: Analyze, design, and build applications and data pipelines using AWS, Databricks ...

K-Tek Resourcing LLC

Senior Data Engineer

Denver, CO · On-site

$45 - $48/hr

Develop high-performance ETL/ELT workflows using Apache Spark and Python. * Write efficient, optimized SQL queries for data extraction, transformation, and analysis. * Build, deploy, and support AI ...

StructureIT

Junior Data Analyst - CMBS

Anton, CO · Hybrid

Extracting of data - We extract data from any file format, including PDF. * Transforming of data - We then clean, restructure, aggregate and classify the data. * Quality Assurance - We perform ...

Summary

Water Conservation Data Analyst

Vail, CO

Advanced skills in querying, data extraction, transformation, aggregation, and optimization * Programming and Analysis: Experience with R and R Studio/VS Code for data manipulation, statistical ...

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All JobsData Extraction JobsData Extraction Jobs in Colorado

Data Extraction information

See Colorado salary details

$10

$26

$65

How much do data extraction jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for data extraction in Colorado is $26.53, according to ZipRecruiter salary data. Most workers in this role earn between $14.26 and $29.42 per hour, depending on experience, location, and employer.

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.

How to become a data extractor?

To become a data extractor, you typically need strong skills in data management, familiarity with data extraction tools like SQL, Python, or specialized software, and attention to detail. Many roles require a high school diploma or higher, and some may prefer certifications in data analysis or related fields. Gaining experience through internships or entry-level positions can also help build relevant skills.

What are the key skills and qualifications needed to thrive in the Data Extraction position, 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.

What is a Data Extraction job?

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 is a data extraction job?

A data extraction job involves retrieving specific information from various sources such as websites, databases, or documents. It often requires skills in using tools like web scrapers or data management software and may involve cleaning and organizing data for analysis or reporting.

What does a data extractor do?

A data extractor is responsible for collecting and retrieving data from various sources such as websites, databases, or documents. They often use tools like web scraping software or data management systems and need strong attention to detail and technical skills. The role involves transforming unstructured data into organized formats for analysis or storage.
What are the most commonly searched types of Data Extraction jobs in Colorado? The most popular types of Data Extraction jobs in Colorado are:
What are popular job titles related to Data Extraction jobs in Colorado? For Data Extraction jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Data Extraction jobs in Colorado look for? The top searched job categories for Data Extraction jobs in Colorado are:
Data Extraction jobs near you
Infographic showing various Data Extraction job openings in Colorado as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $55,175 per year, or $26.5 per hour.
Business (Data) Analyst

Business (Data) Analyst

Apetan Consulting llc

Denver, CO • On-site

$80 - $150/hr

Contractor

Posted 11 days ago

Job description

Job Title : Business (Data) Analyst

Job Location:- Denver, CO (Need only local candidate)

Job Type : Contract

Skills: SQL, SNOWFLAKE, DATABRICKS, AWS, REDSHIFT, DATA WAREHOUSE, ETL

  • Experience: 7+ years
  • Develop Data Solutions: Analyze, design, and build applications and data pipelines using AWS, Databricks, Redshift, and Snowflake.
  • ETL/ELT Development: Analyze standards and procedures for, and design data extraction, transformation, and loading (ETL/ELT) processes for both batch and real-time data.
  • Database Management: Design Data Lakes and Data Warehouses, and work with databases like Oracle and SQL Server.
  • SQL Expertise: Write advanced SQL queries, including performance tuning, to support data analysis and application needs.
  • Full Software Development Lifecycle: Handle the entire SDLC for data warehouse applications, from requirements analysis to implementation, testing, and debugging.
  • System Integration: Integrate, enhance, and fine-tune Enterprise Data Warehouses to consolidate data from various sources.