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Remote Data Extraction Jobs in Dallas, TX (NOW HIRING)

Remote (Needs to travel to client site when required with your own expenses) Duration: Long term ... Monitor, manage, validate and test data extraction, movement, transformation, loading ...

Sr/Staff Data Engineer (Remote - US)

TX · On-site +1

$165K - $300K/yr

Remote US Anticipated Start Date: 06/01/2026 The US base salary range for this full-time position ... Experience with ETL processes and tools including cloud based solutions * Familiarity with database ...

Data Engineer

Dallas, TX · On-site +1

$113K - $136K/yr

In this role, youll develop scalable ETL/ELT workflows feeding Snowflake and Databricks ... Preference is for this to be a hybrid role in Pittsburgh, but we are open to fully remote ...

"DATA ENGINEER"

Dallas, TX · Remote

$117K - $140K/yr

Lead Data Engineer & Sr. Data Engineer Location: Remote Duration: CTH/FTE Type: Only W2 Note ... Strong ETL using SSIS and PySpark * Databricks * Must have Azure (Azure Data Factory, Azure Synapse ...

Senior ML Data Engineer - Remote

Plano, TX · On-site +1

$110K - $132K/yr

Senior ML Data Engineer Feature Engineering ETL Qualifications 7 years in data engineering and at least 4 years focusing on ML feature engineering ETL pipeline development and data preparation for ML ...

Data Engineer - Remote

Dallas, TX · On-site +1

$105K - $126K/yr

Strong understanding of data warehousing concepts, dimensional modeling, and ETL best practices * Proficiency in SQL and at least one programming language (Python or Java) * Hands-on experience with ...

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Remote Data Extraction information

What are some common challenges faced in a remote data extraction role and how can they be addressed?

One common challenge in remote data extraction is ensuring data accuracy while working independently, especially when dealing with large and diverse datasets. Discrepancies can arise from inconsistent data formats or sources, so developing strong attention to detail and utilizing reliable extraction tools is critical. Another challenge is communication, as collaborating with data analysts or project managers remotely requires proactive updates and clear documentation. To address these issues, it's helpful to establish regular check-ins with your team, use standardized data templates, and stay organized with project management software.

What jobs pay 4000 a week without a degree?

Remote data extraction roles can pay around $4,000 per week for experienced professionals, especially those skilled in data scraping, automation tools, and programming languages like Python or SQL. These positions often require strong technical skills, self-motivation, and the ability to work independently, with some roles offering high pay based on project complexity and volume.

How to make $1000 a week remotely?

Remote data extraction jobs can pay between $10 and $25 per hour, so earning $1000 weekly typically requires working 40 to 50 hours. Developing strong data handling skills, familiarity with tools like Excel or data scraping software, and maintaining consistent productivity can help achieve this income level. Building a reliable client base or working through reputable platforms can also increase earning potential.

What is remote data extraction?

Remote data extraction is the process of retrieving and collecting data from various sources—such as websites, databases, or documents—without being physically present at the source location. This is typically achieved using specialized software, scripts, or tools that can access and gather data over the internet or through remote connections. Professionals in this field often automate data collection tasks to save time and improve accuracy, especially when dealing with large volumes of information. Remote data extraction is commonly used for business intelligence, market research, competitive analysis, and data migration projects.

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

To thrive as a Remote Data Extraction Specialist, you need proficiency in data analysis, attention to detail, and experience with data extraction and transformation techniques, often supported by a degree in computer science, information systems, or a related field. Familiarity with tools such as SQL, Python, web scraping frameworks (like BeautifulSoup or Scrapy), and data management platforms is typically required. Strong problem-solving skills, self-motivation, and effective communication are valuable soft skills for excelling in a remote environment. These abilities ensure accurate data collection, efficient workflow, and reliable delivery of insights for business or research needs.

How to become a data extractor?

To become a remote data extractor, you should develop skills in data collection, cleaning, and analysis, often using tools like Excel, SQL, or web scraping software. Relevant experience, attention to detail, and the ability to work independently are important, and some roles may require basic knowledge of programming languages such as Python or JavaScript.

What is the difference between Remote Data Extraction vs Remote Data Entry?

AspectRemote Data ExtractionRemote Data Entry
Primary FocusExtracting data from various sources like websites, PDFs, or imagesInputting data into databases or spreadsheets
Skills RequiredWeb scraping, data analysis, attention to detailTyping speed, accuracy, basic computer skills
Tools UsedWeb scraping software, OCR tools, data management platformsExcel, Google Sheets, data entry software
Work EnvironmentMostly independent, often project-basedConsistent, repetitive tasks

Remote Data Extraction involves retrieving data from various sources, requiring technical skills like web scraping and data analysis. Remote Data Entry focuses on inputting data accurately into systems, emphasizing speed and precision. Both roles are remote-friendly but differ in technical complexity and daily tasks.

Is 40 too late for data science?

Age is not a strict barrier for a remote data extraction or data science role; many professionals transition into the field later in life. Success depends on skills, experience, and continuous learning of tools like Python, SQL, and machine learning concepts, regardless of age.
What are the most commonly searched types of Data Extraction jobs in Dallas, TX? The most popular types of Data Extraction jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Remote Data Extraction jobs? Cities near Dallas, TX with the most Remote Data Extraction job openings:
Infographic showing various Remote Data Extraction job openings in Dallas, TX as of June 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution.

Freelance Data Scraping Engineer (Python)

Mindrift

Dallas, TX • Remote

$37/hr

Part-time

Posted 22 days ago


Job description

Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.

In this role, as an AI Pilot - that's how we refer to this role at Mindrift - you'll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable results.

This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction and processing.

What We Do

The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.

About the Role

This is a freelance role for a Tendem project. As a Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.

Key Responsibilities

  • Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
  • Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.
  • Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.
  • Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.
  • Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.

Compensation

On this project, contributors can earn up to $37 per hour equivalent, depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

How to get started

Simply apply to this post, qualify, and get the chance to contribute to projects that match your technical skills, on your own schedule. From coding and automation to fine-tuning AI outputs, you'll play a key role in advancing AI capabilities and real-world applications.

Requirements

  • At least 3 year of relevant experience in data engineering, web scraping, automation, or software development (required).
  • Bachelor's or Master's Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.
  • Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies.
  • Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML).
  • Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets).
  • Hands-on experience with LLMs and AI frameworks to enhance automation and problem-solving.
  • Strong attention to detail and commitment to data accuracy.
  • Self-directed work ethic with ability to troubleshoot independently.
  • A link to GitHub is a plus.
  • English proficiency: Upper-intermediate (B2) or above (required).

Benefits

Why this freelance opportunity might be a great fit for you?

  • Work fully remote on your own schedule with just a laptop and stable internet connection.
  • Gain hands-on experience in a unique hybrid environment where human expertise and AI agents collaborate seamlessly - a distinctive skill set in a rapidly growing field.
  • Participate in performance-based bonus programs that reward high-quality work and consistent delivery.