Reads like a Data Leadership role: running a data team.
Bengaluru, KA, India
Actively hiring, first seen by us 8 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Lead a team of data engineers building ingestion and transformation pipelines
Build Bronze, Silver and Gold layers in Databricks, including Gold finance data domains
Publish certified data products from Databricks to Snowflake for reporting
Move recurring Dataiku analyst workflows into engineered Databricks pipelines
Set coding standards, code review and CI/CD practices in Azure DevOps
Lead a team of data engineers building ingestion and transformation pipelines
Build the Bronze, Silver and Gold layers in Databricks, including conformed dimensions and Gold data domains
Publish certified data products from Databricks to Snowflake for reporting and analysis
Move recurring Dataiku analyst workflows into engineered Databricks pipelines
Set coding standards, branching, code review and CI/CD practices in Azure DevOps
EXPERIENCE AND QUALIFICATIONS
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.
8 to 12 years in data engineering, with at least 3 years leading teams
Experience on data programmes in banking or financial services
Degree in engineering or computer a
Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 8
Similar jobs usually come down between day 8 and day 57.
Well past WNS Global Services’s usual: its jobs come down by about day 2.
From 9,519 similar postings that came down, and 71 of WNS Global Services’s. Coming down is not always a hire.
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Azure Data Factory Python and advanced SQL Dimensional modelling
Must-have Databricks, including PySpark, Spark SQL, Delta Lake, Workflows and Unity Catalog Snowflake SQL, data loading and performance tuning
Databricks, including PySpark, Spark SQL, Delta Lake, Workflows and Unity Catalog Snowflake SQL, data loading and performance tuning Azure Data Factory
Data Engineering Lead We are looking for a Data Engineering Lead with 8 to 12 years of experience to lead the build of data pipelines for an enterprise finance data platform on Azure, Databricks and Snowflake. You will run the data engineering team, own delivery from source systems through to certified Gold data products, and set the engineering standards the team works to. KEY RESPONSIBILITIES
Lead a team of data engineers building ingestion and transformation pipelines Deliver ingestion from finance source systems using change data capture, Azure Data Factory batch loads, API and event-driven feeds, and governed manual uploads Build the Bronze, Silver and Gold layers in Databricks, including conformed dimensions and Gold data domains
Move recurring Dataiku analyst workflows into engineered Databricks pipelines Set coding standards, branching, code review and CI/CD practices in Azure DevOps Estimate work, plan sprints and report progress to the Engagement Manager
Snowflake SQL, data loading and performance tuning Azure Data Factory Python and advanced SQL
Dimensional modelling Git and CI/CD with Azure DevOps Leading engineering teams in agile delivery
Deliver ingestion from finance source systems using change data capture, Azure Data Factory batch loads, API and event-driven feeds, and governed manual uploads Build the Bronze, Silver and Gold layers in Databricks, including conformed dimensions and Gold data domains Build Gold data domains for financial control, FP&A, tax, recharges and project accounting with the Data Architect
Build Gold data domains for financial control, FP&A, tax, recharges and project accounting with the Data Architect Publish certified data products from Databricks to Snowflake for reporting and analysis Build data quality, reconciliation and matching checks into pipelines with the data quality team
Build data quality, reconciliation and matching checks into pipelines with the data quality team Move recurring Dataiku analyst workflows into engineered Databricks pipelines Set coding standards, branching, code review and CI/CD practices in Azure DevOps
CERTIFICATIONS (GOOD TO HAVE) Databricks Certified Data Engineer Professional SnowPro Advanced: Data Engineer
8 to 12 years in data engineering, with at least 3 years leading teams Delivered at least one cloud data platform on Databricks or Snowflake into production Experience on data programmes in banking or financial services
API Management, Service Bus and Functions Delta Live Tables Dataiku
Good-to-have Informatica CDC and PowerCenter API Management, Service Bus and Functions
Banking finance data, including general ledger, sub-ledgers, intra-group and recharges Finance systems such as SAP ECC, BW and BPC, TM1, Alfa and other lending platforms Treasury and banking data from systems such as TMS, T24 and bank statement feeds
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New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
Data Engineering Lead
We are looking for a Data Engineering Lead with 8 to 12 years of experience to lead the build of data pipelines for an enterprise finance data platform on Azure, Databricks and Snowflake. You will run the data engineering team, own delivery from source systems through to certified Gold data products, and set the engineering standards the team works to.
KEY RESPONSIBILITIES
Lead a team of data engineers building ingestion and transformation pipelines
Deliver ingestion from finance source systems using change data capture, Azure Data Factory batch loads, API and event-driven feeds, and governed manual uploads
Build the Bronze, Silver and Gold layers in Databricks, including conformed dimensions and Gold data domains
Build Gold data domains for financial control, FP&A, tax, recharges and project accounting with the Data Architect
Publish certified data products from Databricks to Snowflake for reporting and analysis
Build data quality, reconciliation and matching checks into pipelines with the data quality team
Move recurring Dataiku analyst workflows into engineered Databricks pipelines
Set coding standards, branching, code review and CI/CD practices in Azure DevOps
Estimate work, plan sprints and report progress to the Engagement Manager
Tune pipeline performance and manage compute usage
Support production issues and handover to the support team
TECHNICAL SKILLS
Must-have
Databricks, including PySpark, Spark SQL, Delta Lake, Workflows and Unity Catalog
Snowflake SQL, data loading and performance tuning
Azure Data Factory
Python and advanced SQL
Dimensional modelling
Git and CI/CD with Azure DevOps
Leading engineering teams in agile delivery
Good-to-have
Informatica CDC and PowerCenter
API Management, Service Bus and Functions
Delta Live Tables
Dataiku
Microsoft Purview
DOMAIN KNOWLEDGE
Banking finance data, including general ledger, sub-ledgers, intra-group and recharges
Finance systems such as SAP ECC, BW and BPC, TM1, Alfa and other lending platforms
Treasury and banking data from systems such as TMS, T24 and bank statement feeds
CERTIFICATIONS (GOOD TO HAVE)
Databricks Certified Data Engineer Professional
SnowPro Advanced: Data Engineer
EXPERIENCE AND QUALIFICATIONS
8 to 12 years in data engineering, with at least 3 years leading teams
Delivered at least one cloud data platform on Databricks or Snowflake into production
Experience on data programmes in banking or financial services
Degree in engineering or computer a
Graduate/Post Graduate
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.
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Bengaluru, KA, India
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