Senior Cloud Data Engineer – Hyderabad
Location: Hyderabad
• Experience: Senior Level
• Openings: 1
Job description
Key
Responsibilities:
Minimum 7+ Years experience in Cloud Data platform
Quickly learn and adapt to new technologies as the Data Team's technology stack evolves,
demonstrating the ability to tackle new challenges. Consider all aspects of usability, scalability,
deployment, integration, maintenance, and automation when integrating new technology stacks.
Demonstrate strong programming skills in at least one language (Python, Scala, Java) and the ability to learn additional languages as needed.
Build and maintain ETL pipelines and data-driven systems utilizing technologies such as Apache Spark, AWS Glue, Athena, Redshift, and AWS Batch.
Expertise in writing complex SQL queries is essential. Manage code on GitHub, with a comprehensive understanding of advanced git operations,
including git-flow, rebasing, and squashing. Implement infrastructure as code using Terraform and utilize AWS Analytics and Data Services like Glue, S3, Lambda,
AWS Batch, Athena, Redshift, DynamoDB, CloudWatch, Kinesis, SQS, SNS, and DMS.
Use Jenkins to implement deployment pipelines and engage in requirements gathering to estimate efforts for integrating new technology stacks.
Design and architect solutions for ML, Data Governance, Deployment/Integration Automations,
and Data Analytics. Explore and learn additional AWS services such as ECS, ECR, and EC2, along with Data Modeling
Minimum 7+ Years experience in Cloud Data platform
Quickly learn and adapt to new technologies as the Data Team's technology stack evolves,
demonstrating the ability to tackle new challenges. Consider all aspects of usability, scalability,
deployment, integration, maintenance, and automation when integrating new technology stacks.
Demonstrate strong programming skills in at least one language (Python, Scala, Java) and the ability to learn additional languages as needed.
Build and maintain ETL pipelines and data-driven systems utilizing technologies such as Apache Spark, AWS Glue, Athena, Redshift, and AWS Batch.
Expertise in writing complex SQL queries is essential. Manage code on GitHub, with a comprehensive understanding of advanced git operations,
including git-flow, rebasing, and squashing. Implement infrastructure as code using Terraform and utilize AWS Analytics and Data Services like Glue, S3, Lambda,
AWS Batch, Athena, Redshift, DynamoDB, CloudWatch, Kinesis, SQS, SNS, and DMS.
Use Jenkins to implement deployment pipelines and engage in requirements gathering to estimate efforts for integrating new technology stacks.
Design and architect solutions for ML, Data Governance, Deployment/Integration Automations,
and Data Analytics. Explore and learn additional AWS services such as ECS, ECR, and EC2, along with Data Modeling