WNS hiring For Data Engineer - Gurgaon

Total Experience - 1-2 Years

Rotational Shifts

Platform Ops Data Engineer

This role involves developing reusable scripts, automation solutions, and integrations using modern tools (e.g., Fivetran, Hightouch) to streamline reporting and data analysis processes.

You will have the autonomy to explore and understand business operations, identify opportunities for improvement, and implement innovative technical solutions that enhance overall data platform efficiency.

Qualified candidates require strong collaboration and communication skills, as you will work closely with cross-functional teams. The ideal candidate is both a team player and a self-starter, capable of driving impactful, customer-centric improvements independently, while also being hands-on with debugging and enhancing existing codebases.

Roles & Responsibilities

• Design, build, and maintain robust ETL pipelines and data architectures using tools such as Azure Databricks, Fivetran, and Hightouch to support seamless data ingestion, transformation, and delivery.
• Develop scalable, reusable data solutions in Databricks leveraging Python and PySpark.
• Collaborate with stakeholders and cross-functional engineering teams to enhance and streamline business operations.
• Identify and implement opportunities for process automation and optimization to improve data flow and reduce manual intervention.
• Contribute to frameworks that enhance the efficiency of data ingestion into the delta lake, as well as its processing and distribution.
• Apply big data technologies such as Hadoop and PySpark to effectively manage and process large volumes of data.
• Document production data logic and associated business processes to bridge knowledge gaps between business users, data engineers, and data collection teams.
• Build, monitor, and maintain scalable cloud-based data architectures, with preferred experience in platforms like Microsoft Azure and Snowflake.
• Independently analyze, debug, and enhance code to ensure timely, effective solutions and maintain production-grade reliability.
• Generate insights by analyzing and interpreting large datasets to support data-driven decision-making across the organization.