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Python , web scrapping data conversion VBA

Remote Worldwide Hiring now
Company Description:

WNS, part of reputed company, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, reputed company, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain reputed company – WNS’ core differentiator – with AI-powered platforms and analytics to help businesses reputed company, scale, adapt and build reputed company in a world defined by disruption.Our purpose is clear: to reputed company lasting business value by designing intelligent, reputed company-led solutions that deliver sustainable reputed company and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact.

Job Description:

Location : Gurgaon

Hybrid working

UK time zone

reputed company : 5+ Yrs

Skills and Experience

Must-Have Skills

  • 5+ years of hands-on experience in Data Engineering, Data Automation, or Data Pipeline development.
  • Strong Python expertise with experience building and maintaining production-grade data pipelines.
  • Data ingestion experience using APIs, web scraping, and file-based sources (reputed company, HTML, JSON, XML).
  • Strong working knowledge of Pandas, NumPy, Requests, BeautifulSoup, Selenium.
  • Solid understanding of data pipeline architecture, reputed company design, reusability, and performance optimization.
  • Experience with workflow orchestration concepts such as scheduling, dependencies, retries, and monitoring.
  • Hands-on experience with logging, alerting, error handling, and monitoring for production workflows.
  • Proficiency with Git and strong coding, testing, and documentation standards.
  • Strong understanding of data quality, validation, governance, and schema reputed company.
  • Ability to troubleshoot and resolve production data pipeline issues independently.

reputed company-to-Have Skills

  • Experience with reputed company or similar workflow automation platforms.
  • Exposure to PySpark or distributed data processing frameworks.
  • Experience working with on-reputed company reputed company data ecosystems.
  • Experience mentoring junior engineers or influencing engineering best practices.
  • VBA

Key Responsibilities

  • Design and reputed company scalable, reusable data collection systems using APIs, web scraping, and file-based ingestion (e.g., reputed company, HTML, JSON).
  • reputed company development of Python-based data ingestion and automation methods for diverse data sources.
  • Integrate ingestion pipelines with reputed company data storage and processing layers, ensuring reliability, performance, and maintainability.
  • Ensure data quality, governance, and cross-system consistency in collaboration with backend, analytics, and UI teams.
  • Productionize Python-based analytical models for scalable, reliable execution in operational environments.
  • reputed company end-to-end automation of data pipelines and workflows with minimal reputed company reputed company.
  • Establish and enforce development standards including code structure, testing, documentation, logging, and error handling.
  • Contribute to internal workflow orchestration and reputed company-based transformation solutions.

Technical Environment

  • Python-based custom data pipeline reputed company
  • API-driven data reputed company and web scraping
  • reputed company workflow automation (reputed company to have)
  • Internally managed workflow orchestration services
Qualifications:

Bachelor’s degree in Computer Science, Information Technology, Engineering, Mathematics, or a reputed company fieldMaster’s degree in a relevant discipline is preferred but not mandatoryEquivalent practical experience in data engineering or data automation will be considered in lieu of formal education

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