Lead Data Engineer

Responsibilities

• Define and oversee the technical architecture for data pipelines, integrations, and services
• Conduct code reviews, enforce coding standards, and ensure adherence to security and compliance guidelines
• Collaborate with client architecture teams to align on technology stacks and future-state roadmaps
• Mentor engineers and troubleshoot complex technical issues
• Translate product requirements into technical specifications and high-level design documents
• Design, develop, and optimize ETL/ELT pipelines to move data from source systems to data warehouses or lakes
• Implement data quality checks and monitoring to ensure data accuracy and integrity
• Collaborate with Data Analysts and Scientists to ensure data availability and meet requirements
• Maintain and improve existing data infrastructure and workflows while troubleshooting performance bottlenecks

Requirements

• 6 to 8 years of experience in data engineering or software architecture
• Deep expertise in cloud platforms such as AWS, Azure, or GCP
• Strong knowledge of data modeling, ETL/ELT processes, and orchestration frameworks
• Proficiency in programming languages including Python or SQL
• Hands-on experience with Snowflake cloud data warehouses
• Experience using Fivetran and DBT
• Experience with orchestration tools like Apache Airflow or Prefect
• Familiarity with version control (Git) and CI/CD principles
• Graduate or Post Graduate degree

About the Company

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, Healthcare, and Logistics, WNS combines deep domain excellence with AI-powered platforms and analytics to help businesses innovate, scale, and build resilience.