Python , web scrapping data conversion VBA

smartrecruiters

Gurgaon, Haryana, India 5 Years Exp Posted 47d ago

Job Description

  • 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 (Excel, HTML, JSON, XML).
  • Strong working knowledge of Pandas, NumPy, Requests, BeautifulSoup, Selenium.
  • Solid understanding of data pipeline architecture, modular 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 evolution.
  • Ability to troubleshoot and resolve production data pipeline issues independently.

 

Nice-to-Have Skills

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

 

Key Responsibilities

 

  • Design and develop scalable, reusable data collection systems using APIs, web scraping, and file-based ingestion (e.g., Excel, HTML, JSON).
  • Lead development of Python-based data ingestion and automation methods for diverse data sources.
  • Integrate ingestion pipelines with enterprise 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.
  • Enable end-to-end automation of data pipelines and workflows with minimal manual intervention.
  • Establish and enforce development standards including code structure, testing, documentation, logging, and error handling.
  • Contribute to internal workflow orchestration and Decisions-based transformation solutions.

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