Azure Data Engineer
Gurgaon, India
WNS Global Services
Company Description
WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees.
Job Description
Roles and Responsibilities
- Build ETL & data pipelines using Azure Data Factory & Databricks to help feed the data into data products/dashboards
- Automate processes and workflows to drive efficiencies for client
- Liaise with different stakeholders on ad-hoc analyses and monitor the entire DWH/Data Lake
- Working with stakeholders to gather requirements, provide efficient data solutions and designing the build
- Use best practices to deliver results, efficiency and quality for data and visualization requirements
- Collaborate and support the analytics team to help them understand the data flow
Desired Profile
- Design data pipelines with Azure services including Azure Data Factory and Databricks
- Strong expertise and experience on transforming data using PySpark scripts and SQL queries
- Creating data models/data objects in Azure Synapse/DWH/DB supporting BI/client reporting
- Understanding of data architecture, data modeling, DWH and ELT/ETL concepts
Qualifications
Bachelors
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Azure Banking Databricks Data pipelines ELT ETL Finance Pipelines PySpark SQL
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