WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence – WNS’ core differentiator – with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes 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.

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

Bachelor’s degree in Computer Science, Information Technology, Engineering, Mathematics, or a related 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