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Python Scraping Jobs in California (NOW HIRING)

General Atomics

Engineer I

Poway, CA · On-site

$62K - $105K/yr

... computing * visualizations scraping a database to compare simulated vs. test-logged data ... Familiarity with Python. * Familiarity with SQL databases or similar data-management tools.

Sim

Founding GTM Engineer

San Francisco, CA · On-site

$120K - $200K/yr

Proficiency writing code (Python, JavaScript, or SQL) and familiarity working with APIs * Track ... Experience with modern GTM tools (Clay, Claude Code, Parallel, Unify, Sim, scraping/indexing the ...

Astrana Health

Sr. Software Engineer

Monterey Park, CA · Hybrid

$180K - $210K/yr

Python, React, Javascript, SQL * Bachelor's degree in Computer Science or related, or related ... scraping and other automation scripting, ETL and data pipelines, data science, machine learning

Walmart

Manager, Data Analytics

Sunnyvale, CA · On-site

Experience automating critical pricing workflows using SQL and Python, including data ingestion ... Experience monitoring competitor pricing data sourced from web scraping and syndicated feeds.

Anthropic

Threat Intelligence Engineer

San Francisco, CA · On-site +1

$320K - $405K/yr

Have strong coding proficiency in Python and SQL for building detection logic, data pipelines, and ... Familiarity with web scraping and data extraction at scale * Experience with behavioral analytics ...

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All JobsPython Scraping JobsPython Scraping Jobs in California

Python Scraping information

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$13

$57

$85

How much do python scraping jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for python scraping in California is $57.85, according to ZipRecruiter salary data. Most workers in this role earn between $47.69 and $65.72 per hour, depending on experience, location, and employer.

What are some common challenges faced by Python Scraping professionals, and how can they be addressed?

Python Scraping professionals often encounter obstacles such as website anti-scraping measures, dynamic content loading with JavaScript, and frequent changes in website structures. Overcoming these challenges typically involves using tools like Selenium or Playwright for dynamic pages, rotating proxies and user agents to avoid detection, and writing adaptable, modular code to quickly update scrapers when site layouts change. Staying up to date with the latest libraries and best practices is vital for efficiency and compliance with legal and ethical standards.

What are the key skills and qualifications needed to thrive as a Python Scraping Specialist, and why are they important?

To thrive as a Python Scraping Specialist, you need strong proficiency in Python programming, understanding of web protocols (HTTP, HTML, CSS), and experience with libraries such as BeautifulSoup, Scrapy, or Selenium. Familiarity with version control systems like Git and knowledge of data storage formats (JSON, CSV, SQL) are also commonly required. Problem-solving, attention to detail, and effective communication are valuable soft skills in this role. These skills ensure efficient data extraction, compliance with website policies, and the ability to deliver actionable insights from web data.

What is the difference between Python Scraping vs Data Analyst?

AspectPython ScrapingData Analyst
Required SkillsPython programming, web scraping libraries (BeautifulSoup, Scrapy)Data analysis, SQL, Excel, statistical skills
Work EnvironmentTechnical, coding-focused, often remoteBusiness-focused, reporting, presentations
Industry UsageWeb data extraction, research projectsBusiness insights, decision-making
CertificationsPython certifications, web scraping coursesData analysis certifications (e.g., CAP, Microsoft Certified)

Python Scraping involves writing code to extract data from websites, focusing on programming skills and technical tools. Data Analysts interpret and visualize data for business insights, requiring analytical and statistical skills. While both roles work with data, Python Scraping is more technical and coding-intensive, whereas Data Analysts focus on analyzing and presenting data for decision-making.

What is Python scraping?

Python scraping refers to the process of using the Python programming language to extract data from websites or online sources. It typically involves sending HTTP requests to webpages, parsing the HTML or other content, and collecting specific information for analysis or storage. Popular Python libraries for web scraping include BeautifulSoup, Scrapy, and Requests. This technique is widely used in data analysis, research, and business intelligence, but it's important to respect website terms of service and legal guidelines when scraping data.
What are popular job titles related to Python Scraping jobs in California? For Python Scraping jobs in California, the most frequently searched job titles are:
What job categories do people searching Python Scraping jobs in California look for? The top searched job categories for Python Scraping jobs in California are:
What cities in California are hiring for Python Scraping jobs? Cities in California with the most Python Scraping job openings:
Python Scraping jobs near you
Infographic showing various Python Scraping job openings in California as of July 2026, with employment types broken down into 1% Internship, 88% Full Time, 6% Part Time, 1% Temporary, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $120,336 per year, or $57.9 per hour.
Software Development Engineer - Data Acquisition & Normalization

Software Development Engineer - Data Acquisition & Normalization

ID.me

Mountain View, CA • On-site

$135K - $162K/yr

Other

Re-posted 4 days ago

ID.me rating

5.6

Company rating: 5.6 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

195th of 209 rated software companies

Job description

Role Overview

ID.me is seeking a Software Development Engineer III to join the Data Acquisition & Normalization team. This team is responsible for building and operating the integrations that power the Identity Trust Graph - acquiring, normalizing, and refreshing identity attributes from authoritative and commercial sources.

In this role, you will contribute to building and maintaining connectors, data pipelines, and normalization services that ensure ID.me delivers reliable, real-time validation of identity attributes at internet scale. You will work alongside experienced engineers and partner with Product Managers from the Persons and Organizations teams to help translate validation contracts into working integrations.

This position is based in our Mountain View, CA office, 5 days per week.

Key Responsibilities
  • Build and maintain connectors to government registries, telcos, licensing authorities, and commercial data providers.
  • Standardize and reconcile heterogeneous data formats into clean schemas usable by the Identity Trust Graph.
  • Monitor and help resolve upstream source changes; contribute to retries, fallbacks, and error handling to improve pipeline reliability.
  • Contribute to the Attribute Validation Service (AVS) by adding trusted data that validates identity attributes against sources of record.
  • Help deliver clean and validated attribute data to downstream consumers including Wallet, Fraud, and Domains.
  • Assist in reporting coverage and freshness metrics to Product, Ops, and Analytics stakeholders.
  • Handle sensitive data in accordance with NIST, ISO 27001, and FedRAMP standards.
  • Write high-quality, maintainable, and well-tested code, including automated tests and observability instrumentation.
  • Participate in system design discussions, code reviews, and technical documentation to support team alignment.
Key Success Metrics
  • Attribute coverage and freshness SLA attainment.
  • Connector uptime and reliability.
  • Validation latency and success rates.
  • MTTR (mean time to resolution) for broken integrations.
  • Cost efficiency per validation event.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).
  • 4+ years of experience developing web applications using OOP languages such as Java, Ruby, JavaScript, TypeScript, Go, Python, Rust, or C++.
  • Exposure to data acquisition or integration work, including APIs, screen scraping, ETL, or normalization pipelines.
  • Experience building systems in Docker, Kubernetes or Nomad and services in a containerized, cloud-based, infrastructure-as-code driven ecosystem such as GCP.
  • Ability to deliver features end to end, including automated test coverage, observability, monitoring, and documentation.
  • Ability to communicate technical tradeoffs clearly and work collaboratively within a team.
  • Proficiency and strong interest in AI-assisted development tools (e.g., Claude Code or Codex) to accelerate delivery and code quality.
Preferred Qualifications
  • Familiarity with operating data pipelines with reliability and SLA requirements.
  • Understanding of distributed systems concepts, caching, asynchronous processing, and cloud-native patterns.
  • Exposure to authentication and authorization standards (OAuth2, OIDC, JWT, or custom schemes).
  • Familiarity with identity and credential verification systems, including data validation, proofing, or trust scoring.
  • Exposure to event-driven architectures (Kafka, SNS/SQS) and patterns for decoupled service communication.
  • Experience with cloud infrastructure (AWS, GCP, or Azure), including containerization and deployment pipelines.
  • Familiarity with observability, monitoring, and incident response best practices.
  • Awareness of compliance and security requirements for sensitive data (NIST, FedRAMP, ISO 27001).
  • Bonus: Exposure to FinTech, identity, or data aggregation companies (e.g., Plaid, Yodlee, Envestnet).

What ID.me employees say

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