Quest Global
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Chennai · On-site · 3-5 Yrs · Aug 18
Information Technology Support Services · 10000+ Employees · Singapore, Singapore
At Quest Global, it's not just what we do but how and why we do it that makes us different. We're in the business of engineering, but what we're really creating is a brighter future. For over 25 years, we've been solving the world's most complex engineering problems. Operating in over 20 countries, with over 100 global delivery centers, our 22,000+ curious minds embrace the power of doing things differently to make the impossible possible. Using a multi-dimensional approach, combining technology, industry expertise, and diverse talents, we tackle critical challenges faster and more effectively. And we do it across the Aerospace & Defense, Automotive, Energy, Hi-Tech, MedTech & Healthcare, Rail and Semiconductor industries. For world-class end-to-end engineering solutions, we are your trusted partner.
Hiring: Engineering
What employees say
+ Good to work for carrier initial stage
− Compensations and benefits will be less
More reviews on the company profile.
Interview experience · Data Analyst
It was good. The process was not that tough and it was quick onboarding for me as a data analyst. The interview questions were easy and the HR round was good too.
Average difficulty · Bengaluru · 596 reports
More interview insightsJob description
Overview
Senior Data Engineer with experience in designing and developing scalable data processing solutions using PySpark in Microsoft Fabric. Experience in building ETL/ELT pipelines for large-scale structured and semi-structured datasets.
Responsibilities
- Design and develop scalable data processing solutions using PySpark in Microsoft Fabric.
- Build and optimize ETL/ELT pipelines using Spark DataFrames, Spark SQL.
- Develop workflows for data ingestion, transformation, and aggregation using Fabric Notebooks, Lakehouse, and Data Factory Pipelines.
Qualifications
- Hands-on experience in designing and developing scalable data processing solutions with PySpark in Microsoft Fabric.
- Experience building ETL/ELT pipelines for structured and semi-structured datasets using Spark DataFrames and Spark SQL.
- Experience in data ingestion, transformation, and aggregation workflows.
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