7 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design and implement scalable data architectures using AWS services.
- Build and maintain end-to-end batch and streaming data pipelines.
- Ensure data quality, integrity, and security across data platforms.
- Optimize data storage and processing for performance and cost efficiency.
- Translate cross-functional data requirements into technical solutions.
- Support analytics, reporting, and machine learning use cases with well-structured datasets.
- Monitor, troubleshoot, and improve existing data workflows and systems.
Requirements
- Strong hands-on experience with AWS data services including S3, Glue, Redshift, Athena, Lambda, and EMR.
- Experience building scalable ETL/ELT pipelines using Python, Spark, or SQL.
- Knowledge of relational and NoSQL databases, data modeling, and data warehouse concepts.
- Experience with big data frameworks and streaming technologies such as Spark, Kafka, and Kinesis.
- Familiarity with CI/CD, infrastructure as code using Terraform or CloudFormation, and monitoring tools.
Benefits
- Career paths and internal opportunities within the Capgemini group.
- Personalized career guidance from organizational leaders.
- Comprehensive wellness benefits including health checks, telemedicine, insurance top-ups, elder care, partner coverage, and new parent support through flexible work.
- Opportunities to work on technology and engineering projects with industry leaders and societal or environmental impact initiatives.
Tech Stack
Categories
Data Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.