Assistant Manager - Sr. Data Engineering | Databricks | ADF | Snowflake

Company Description

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.

Why Join Us?

We promise our employees to experience role clarity, coaching and mentoring, professional development and structured career path through our 5 people promises and keeping employee experience at the core. Experience the culture of Outperformance, engagement, celebration and enjoy wide variety of best in class benefits including free HMO coverage for self and dependent from Day 1; Also contribute to society through our WNS Cares Foundation, where you have the opportunity to support meaningful initiatives and make an impact in the community.

Job Description

Senior Data Engineer

We are looking for a Senior Data Engineer with 4 to 5 years of experience to build data pipelines for an enterprise finance data platform on Azure, Databricks and Snowflake. You will develop ingestion and transformation jobs, build Gold data products and publish them to Snowflake for reporting.

KEY RESPONSIBILITIES

Build ingestion pipelines from finance source systems using Azure Data Factory, change data capture, and API and event-driven feeds

Develop transformations in Databricks across the Bronze, Silver and Gold layers using PySpark and Spark SQL

Build conformed dimensions and fact tables to the agreed data model

Load certified Gold data into Snowflake and build the views used by reporting teams

Add data quality, reconciliation and logging checks to pipelines

Write unit tests and support system and user acceptance testing

Follow coding standards and take part in code reviews

Deploy code through Azure DevOps pipelines

Investigate and fix pipeline failures and data issues

Document pipelines, mappings and run procedures

TECHNICAL SKILLS

Must-have

Databricks, including PySpark, Spark SQL and Delta Lake

Azure Data Factory

Snowflake SQL and data loading

Python and advanced SQL

Dimensional modelling

Git and Azure DevOps

Good-to-have

Informatica CDC

Azure Functions and Service Bus

Unity Catalog

Delta Live Tables

Power BI

DOMAIN KNOWLEDGE

Finance data such as general ledger, trial balance, sub-ledgers and bank statements

Finance source systems such as SAP, TM1 and lending platforms

CERTIFICATIONS (GOOD TO HAVE)

Databricks Certified Data Engineer Associate

SnowPro Core

EXPERIENCE AND QUALIFICATIONS

4 to 5 years in data engineering, with at least 2 years on Databricks or Snowflake

Worked on at least one cloud data platform project that went into production

Degree in engineering or computer applications (B.E., B.Tech or MCA) 

Qualifications

Degree in engineering or computer applications (B.E., B.Tech or MCA)