Total 1 web editor job vacancies in Information Technology category in Gurgaon

Location : Gurgaon

Hybrid working

UK time zone

Exp : 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 (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.

Technical Environment

• Python-based custom data pipeline framework
• API-driven data access and web scraping
• Decisions workflow automation (nice to have)
• Internally managed workflow orchestration services