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Web Scraping Engineer Jobs in Austin, TX (NOW HIRING)

Gather data from various sources (SQL databases, APIs, web scraping), then clean and "wrangle" it ... Programming: Proficiency in Python or R along with SQL for database querying. * Mathematics ...

Gather data from various sources (SQL databases, APIs, web scraping), then clean and "wrangle" it ... Programming: Proficiency in Python or R along with SQL for database querying. * Mathematics ...

Python Tutor

Austin, TX · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

Round Rock, TX · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

San Marcos, TX · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Web Scraping Engineer information

See Austin, TX salary details

$11

$58

$85

How much do web scraping engineer jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for web scraping engineer in Austin, TX is $58.49, according to ZipRecruiter salary data. Most workers in this role earn between $50.77 and $66.25 per hour, depending on experience, location, and employer.

What does a web scraping engineer do?

A Web Scraping Engineer designs and develops software tools or scripts to automatically extract data from websites. They work with programming languages like Python and use libraries such as BeautifulSoup or Scrapy to gather and process web data efficiently. In addition to building scrapers, they also handle challenges such as dealing with website restrictions, CAPTCHAs, and ensuring compliance with legal and ethical guidelines. Their work is often used for market research, data analysis, or feeding information into business applications.

What are some common challenges faced by web scraping engineers when extracting data from dynamic websites?

Web Scraping Engineers often encounter challenges such as navigating websites that use JavaScript to load content dynamically, dealing with anti-bot measures like CAPTCHAs or IP blocking, and ensuring data accuracy as website structures frequently change. To address these issues, engineers typically use headless browsers, rotating proxies, and robust error handling strategies. Staying up-to-date with the latest web technologies and adapting scripts proactively are essential for long-term success in this role.

What are the key skills and qualifications needed to thrive as a web scraping engineer, and why are they important?

To thrive as a Web Scraping Engineer, you need strong programming skills (especially in Python), knowledge of data extraction techniques, and familiarity with web protocols and HTML structure. Expertise with tools like Scrapy, BeautifulSoup, Selenium, and experience with APIs or anti-bot evasion techniques is typically required. Attention to detail, problem-solving, and strong analytical thinking are essential soft skills in this field. These skills ensure efficient, ethical, and reliable extraction of data from diverse web sources while navigating technical and legal complexities.

What is the difference between Web Scraping Engineer vs Data Engineer?

AspectWeb Scraping EngineerData Engineer
Primary FocusDeveloping and maintaining web scraping tools to extract data from websitesBuilding and managing data pipelines and infrastructure for data storage and processing
Skills & CertificationsPython, APIs, HTML, CSS, web scraping libraries (BeautifulSoup, Scrapy)SQL, ETL tools, cloud platforms, programming (Python, Java)
Work EnvironmentTech companies, data-driven startups, research projectsLarge enterprises, data warehouses, cloud environments
Industry UsageData collection for analytics, research, competitive analysisData integration, analytics, machine learning pipelines

While both roles involve working with data, a Web Scraping Engineer specializes in extracting data from websites using scraping tools, whereas a Data Engineer focuses on building data pipelines and infrastructure for storing and processing large datasets. The roles often overlap in skills like Python programming but serve different core functions within data ecosystems.

What job categories do people searching Web Scraping Engineer jobs in Austin, TX look for?

The top searched job categories for Web Scraping Engineer jobs in Austin, TX are:

What cities near Austin, TX are hiring for Web Scraping Engineer jobs?

Cities near Austin, TX with the most Web Scraping Engineer job openings:

Freelance Data Scraping Engineer (Python)

Mindrift

Austin, TX • Remote

$37/hr

Part-time

Re-posted 8 days ago


Job description

Mindrift is looking for highly skilled Web Scraping specialists to join the Tendem project (https://tendem.ai/) and drive specialized data scraping workflows for real-world use cases.

Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows for real-world applications.

In this role, you'll apply your expertise in web scraping, data extraction, and data processing to deliver accurate, reliable, and high-quality 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 innovative technology projects. Our mission is to help develop high-quality AI technologies by combining real-world expertise from professionals across the globe with advanced AI development efforts.

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 tools such as Apify, OpenRouter, and other technologies, alongside your own technical expertise and approaches. 

Key Responsibilities

  • Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
  • Leverage available tools and 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.

Educational qualifications

  • At least 3+ years 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.

Academic and/or Professional Experience

Candidates should have a strong technical foundation and practical experience with scripting, automation, and data extraction workflows. We are looking for specialists who can solve non-trivial problems, work confidently with modern web technologies and data processing tools, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.

Technical Skills (Essential)

  • 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)

Additional requirements

  • 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)

Project time expectations 

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.

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.