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975 KPMG India Jobs
Senior - AWS Data Engineering
KPMG India
posted 12hr ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
- Evaluating, developing, maintaining and testing data engineering solutions for Data Lake and advanced analytics projects.
- Implement processes and logic to extract, transform, and distribute data across one or more data stores from a wide variety of sources
- Distil business requirements and translate into technical solutions for data systems including data warehouses, cubes, marts, lakes, ETL integrations, BI tools or other components.
- Creation and support of data pipelines built on AWS technologies including Glue, Redshift, EMR, Kinesis and Athena
- Participate in deep architectural discussions to build confidence and ensure customer success when building new solutions and migrating existing data applications on the AWS platform.
- Optimize data integration platform to provide optimal performance under increasing data volumes
- Support the data architecture and data governance function to continually expand their capabilities
- Experience in development of Solution Architecture for Enterprise Data Lakes (applicable for AM/Manager level candidates)
- Should have exposure to client facing roles
- Strong communication, inter-personal and team management skills
- Proficient in any object-oriented/ functional scripting languages: Pyspark, Python etc.
- Experience in using AWS SDKs for creating data pipelines - ingestion, processing and orchestration.
- Hands on experience in working with big data on AWS environment including cleaning / transforming / cataloguing / mapping etc.
- Good understanding of AWS components, storage (S3) & compute services (EC2)
- Hands on experience in AWS managed services (Redshift, Lambda, Athena) and ETL (Glue).
- Experience in migrating data from on-premise sources (e.g. Oracle, API-based, data extracts) into AWS storage (S3).
- Experience in setup of data warehouse using Amazon Redshift, creating Redshift clusters and perform data analysis queries.
- Experience in ETL and data modelling on AWS ecosystem components - AWS Glue, Redshift, DynamoDB.
- Experience in setting up AWS Glue to prepare data for analysis through automated ETL processes.
- Familiarity with AWS data migration tools such as AWS DMS, Amazon EMR, and AWS Data Pipeline.
- Hands on experience with AWS CLI, Linux tools and shell scripts.
- Certifications on AWS will be an added plus.
Employment Type: Full Time, Permanent
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