Deputy Manager-Data Engineering
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.
Job Description:Deputy Manager - RNA ( Data Engineer )
Exp - 5 - 8 Years
Location - Gurgoan
Essential skills
Azure Databricks — pipeline development, jobs, notebooks, and optimisation
Azure Data Factory (ADF) — pipeline design, triggers, transformations
Python and SQL — data transformation, quality logic, schema management•
ETL/ELT pipeline design — end-to-end ownership including ingestion, transformation, delivery•
Data quality frameworks — validation rules, alerting, exception handling• Pipeline orchestration and scheduling•
Azure cloud — resource management, Key Vault, Monitor•
Git and version control — branching, code review practicesDesirable skills•
Apache Airflow or equivalent orchestration tooling•
PySpark for large-scale data transformation•
Nielsen or third-party market data integration experience• Pricing, NRM, or commercial data domain familiarity•
Experience with market onboarding or multi-territory data configurationExperience & ways of working•
5–8 years in data engineering roles with end-to-end pipeline ownership in Azure cloud environments•
Must have experience owning pipelines in production — including monitoring, incident response, and on-call support•
Comfortable working directly with business and technical stakeholders to understand and implement data requirements•
Experience building pipelines that serve real-time or near-real-time analytics applications• Strong documentation discipline — runbooks, data dictionaries, and pipeline architecture records
Qualifications:Bachelors in Computer Science, B Tech, MCA M Tech
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