AWS Data Engineer
at Capgemini
London, England, United Kingdom -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 02 Feb, 2025 | Not Specified | 03 Nov, 2024 | 5 year(s) or above | Data Storage Technologies,Python,Data Warehouse,Programming Languages,Java,Scala,Hadoop | No | No |
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Description:
THE JOB YOU’RE CONSIDERING
The Cloud Data Platforms team is part of the Insights and Data Global Practice and has seen strong growth and continued success across a variety of projects and sectors. Cloud Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers digital and data transformation journey using the modern cloud platforms. We specialise on using the latest frameworks, reference architectures and technologies using AWS, Azure and GCP.
YOUR SKILLS AND EXPERIENCE
- Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions.
- Programming Skills: Strong experience with modern programming languages such as Python, Java, and Scala.
- Expertise in Data Storage Technologies: In-depth knowledge of Data Warehouse, Database technologies, and Big Data Eco-system technologies such as AWS Redshift, AWS RDS, and Hadoop.
- Experience with AWS Data Lakes: Proven experience working with AWS data lakes on AWS S3 to store and process both structured and unstructured data sets.
Responsibilities:
We are looking for strong AWS Data Engineers who are passionate about Cloud technology. Your work will be to:
- Design and Develop Data Pipelines: Create robust pipelines to ingest, process, and transform data, ensuring it is ready for analytics and reporting.
- Implement ETL/ELT Processes: Develop Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) workflows to seamlessly move data from source systems to Data Warehouses, Data Lakes, and Lake Houses using Open Source and AWS tools.
- Adopt DevOps Practices: Utilize DevOps methodologies and tools for continuous integration and deployment (CI/CD), infrastructure as code (IaC), and automation to streamline and enhance our data engineering processes.
- Design Data Solutions: Leverage your analytical skills to design innovative data solutions that address complex business requirements and drive decision-making.
REQUIREMENT SUMMARY
Min:5.0Max:10.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Proficient
1
London, United Kingdom