Senior Data Scientist Engineer

Capgemini; Bengaluru; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

Capgemini in Bengaluru seeks a data engineering/data science professional to design and implement data analytics solutions using Python, PySpark, and SQL. You will build scalable ETL pipelines and collaborate across teams to transform data into business insights.

The role requires cloud familiarity (Azure/AWS/GCP) and CI/CD practices to deliver reliable data products on cloud platforms, with a focus on performance optimization and scalable architectures.

Qualifications

• Strong hands-on experience in Python, PySpark, SQL, Data Science, and Data Analysis.
• Experience building and maintaining ETL/data integration pipelines.
• Hands-on experience with Azure/Microsoft data services and cloud-based data solutions.
• Working knowledge of AWS, Azure, or Google Cloud (GCP) and cloud data platforms.
• Good understanding of CI/CD, data processing, performance optimization, and analytical problem-solving.

Responsibilities

• Develop and implement Data Science and Data Analytics solutions using Python, PySpark, and SQL.
• Build and optimize scalable ETL and data processing pipelines for large datasets.
• Perform data analysis, transformation, feature engineering, and statistical analysis to generate business insights.
• Design and deploy data solutions using Azure/Microsoft Services, AWS, Azure, or GCP.
• Implement CI/CD pipelines and collaborate with engineering and business teams to deliver reliable data solutions.

Skills

Python

PySpark

SQL

Data Science

Data Analysis

CI/CD

ETL pipelines

Tools

Azure

AWS

GCP

Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired bya collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds leading organizations

Your Role

• Develop and implement Data Science and Data Analytics solutions using Python, PySpark, and SQL.
• Build and optimize scalable ETL and data processing pipelines for large datasets.
• Perform data analysis, transformation, feature engineering, and statistical analysis to generate business insights.
• Design and deploy data solutions using Azure/Microsoft Services, AWS, Azure, or GCP.
• Implement CI/CD pipelines and collaborate with engineering and business teams to deliver reliable data solutions.

Your Profile

• Strong hands-on experience in Python, PySpark, SQL, Data Science, and Data Analysis.
• Good experience in developing and maintaining ETL/data integration pipelines.
• Hands-on experience with Azure/Microsoft data services and cloud-based data solutions.
• Working knowledge of AWS, Azure, or Google Cloud (GCP) and cloud data platforms.
• Good understanding of CI/CD, data processing, performance optimization, and analytical problem-solving.