Job Description

Senior - AWS+Redshift

Description

About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

Equal employment opportunity information

KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.

Data Engineer – AWS

Role & REsPonsibilty

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

THE INDIVIDUAL

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.

Responsibilities

About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.

Equal employment opportunity information

KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.

Data Engineer – AWS

Role & Responsibilty

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

THE INDIVIDUAL

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.