This is a remote position; however, the candidate must reside within 30 miles of one of the ... Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging ...
This is a remote position; however, the candidate must reside within 30 miles of one of the ... Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging ...
Business Intelligence Analyst
Southlake, TX · Remote
$70K/yr
Work remote * Competitive annual salary: $70,000, paid weekly * Next day payon demandwithDailyPay ... Manage and execute web scraping activities using internal tools to gather competitive intelligence ...
Business Intelligence Analyst
Southlake, TX · Remote
$70K/yr
Work remote * Competitive annual salary: $70,000, paid weekly * Next day payon demandwithDailyPay ... Manage and execute web scraping activities using internal tools to gather competitive intelligence ...
Remote Web Scraping information
See Texas salary details
$10.75 - $17.10
4% of jobs
$17.10 - $23.45
0% of jobs
$23.45 - $29.81
0% of jobs
$29.81 - $36.16
6% of jobs
$36.16 - $42.51
5% of jobs
$47.41 is the 25th percentile. Wages below this are outliers.
$42.51 - $48.86
12% of jobs
The median wage is $55.07 / hr.
$48.86 - $55.22
23% of jobs
$61.25 is the 75th percentile. Wages above this are outliers.
$55.22 - $61.57
26% of jobs
$61.57 - $67.92
13% of jobs
$67.92 - $74.27
3% of jobs
$74.27 - $80.62
7% of jobs
$10
$54
$80
How much do remote web scraping jobs pay per hour?
What is a Remote Web Scraping job?
A Remote Web Scraping job involves extracting data from websites using automated scripts or software while working from a remote location. Professionals in this field write and maintain web scrapers to collect structured information for businesses, research, or competitive analysis. They often use programming languages like Python and tools such as BeautifulSoup, Scrapy, or Selenium. Compliance with legal and ethical guidelines, including respecting robots.txt files and avoiding excessive server requests, is essential.
What are the key skills and qualifications needed to thrive in the Remote Web Scraping position, and why are they important?
To thrive in Remote Web Scraping, you need strong programming skills in languages such as Python, along with a solid understanding of HTML, CSS, and data extraction techniques. Familiarity with tools like Scrapy, Selenium, BeautifulSoup, and knowledge of database systems or cloud platforms is highly valuable. Attention to detail, problem-solving abilities, and effective communication skills help set top candidates apart. These competencies ensure efficient, ethical collection of data while adapting to evolving website structures and collaborating with distributed teams.
What are the typical daily responsibilities for someone working in remote web scraping?
In a remote web scraping role, your typical day involves designing and developing automated scripts to extract data from various websites, cleaning and structuring the gathered information, and collaborating with team members to interpret and deliver results. You’ll often troubleshoot changes in website structure, monitor for errors, and ensure that your scraping activities adhere to the latest legal and ethical standards. Communication with project managers and data analysts is common, as your work directly supports broader business intelligence initiatives. Many roles also encourage learning and staying updated with new tools or methods, providing plenty of opportunity for skills development.

Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 2 days ago
Job description
This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA.
About the Team/Role
As WEX continues to scale its Data-as-a-Service (DaaS) platform, the Data Acquisition Team plays a critical role in enabling secure, scalable, and reliable ingestion of data from hundreds of internal systems and external sources.
We are seeking a hands-on Senior Manager, Software Engineering - Data Acquisition to lead our team in acquiring and processing high-volume data, while simultaneously driving the evolution toward AI-augmented, spec-driven software development to enhance platform scalability and delivery speed.
This role requires a strong leader with deep technical expertise in data pipelines, distributed systems, and cloud architecture, who can drive technical excellence, foster a culture of innovation, and align the data acquisition strategy with overall business goals.
Responsibilities:
Engineering Leadership & Team Development: Recruit, mentor, and lead a high-performing team of software engineers focused on data acquisition, fostering a collaborative and inclusive culture. Oversee performance management, career pathing, and top-tier talent acquisition.
AI-Augmented Development Strategy: Pioneer the adoption of AI-assisted software development across engineering teams. Define metrics and implement AI-enabled development workflows to measurably enhance engineering productivity.
Specification-Driven Development (SDD): Establish and enforce a specification-first development methodology. Standardize templates for all key artifacts (APIs, data contracts, ingestion pipelines, architecture) and ensure end-to-end traceability across implementation, validation, deployment, and observability.
Architectural Transformation & Modernization: Drive the migration to automated, metadata-driven, and declarative engineering architectures. Develop reusable frameworks that translate technical specifications directly into generated code, deployment artifacts, and operational controls.
Strategic Roadmap Execution: Define and execute the technical roadmap for all data acquisition pipelines and systems, ensuring the infrastructure is highly scalable, reliable, secure, and cost-effective to accommodate accelerating data volume and velocity.
Technical Governance & Oversight: Provide authoritative technical direction on the design, development, and maintenance of mission-critical data ingestion frameworks. Mandate and enforce best practices for software engineering, data governance, and data quality.
Stakeholder Collaboration: Partner closely with Product Management, Data Science, Data Governance, and other engineering teams to align data solutions with overarching business requirements and strategic data needs.
Engineering Process Optimization: Institute and champion continuous improvement in engineering processes, tools, and methodologies, including CI/CD, automation, monitoring, and alerting practices.
Sustained Operational Excellence: Guarantee the high availability and performance of all data acquisition systems, taking ownership of incident response, recovery, and thorough root cause analysis for major service disruptions.
Resource & Financial Stewardship: Oversee budget allocation, resource management, and capacity planning to ensure the strategic growth of the data acquisition organization.
Qualifications:
Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
Experience: 10+ years of experience in software engineering, with at least 5+ years in a management role overseeing software engineering or data acquisition teams.
Experience in leading virtual teams is highly desirable
Technical Expertise:
Experience implementing AI-assisted engineering workflows in production software organizations.
Deep understanding of specification-driven engineering, declarative system design, or model-driven development.
Deep expertise in building and managing high-volume, real-time and batch data pipelines (e.g., Kafka, Kinesis, Pulsar).
Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and experience designing scalable, serverless, or containerized data ingestion architectures (e.g., Kubernetes, EKS/AKS/GKE).
Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging queues), and ETL/ELT tools.
Expertise in programming languages such as Java, Python, Scala, or Go.
Solid understanding of database technologies (SQL, NoSQL, Data Warehouses like Snowflake, Redshift, etc.).
Leadership Skills: Proven ability to lead, motivate, and manage multiple distributed teams. Excellent communication, presentation, and interpersonal skills.
Problem Solving: Strong analytical and problem-solving skills, with the ability to define solutions for complex technical challenges.