Data Engineering - AWS DMS

HCLTech is looking for a highly talented and self-motivated Data Engineering AWS DMS professional to join its team in advancing the technological world through innovation and creativity. The role involves developing services for data ingestion, implementing scalable data pipelines, and collaborating with business owners on data architecture.

Responsibilities:

• Develop Services to enable data ingestion from and synchronization with system which exposes required data access mechanisms ensuring near-real-time updates
• Ingest data from multiple sources using the python and any other ETL tools
• Design and implement an event-driven architecture using AWS EventBridge, Kafka, or SNS/SQS for real-time data streaming
• Design, implement, and maintain scalable data pipelines that integrate both on-prem and AWS cloud environments
• Develop efficient Python scripts and applications using libraries like pandas, NumPy, etc., to handle and process large datasets
• Work with various NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB) to support high-performance data storage and retrieval
• Develop and deploy applications in a cloud-native architecture, leveraging modern cloud technologies for scalability and resilience
• Continuously monitor data workflows and systems, troubleshoot issues, and optimize performance for reliability and scalability
• Transition existing pipeline to MSSQL server
• Collaborate with the business application owner on the existing data architecture, including data ingestion, data pipelines, business logic, data consumption patterns, and analytics requirements
• Design and document the target data architecture, pipelines, processing and analytics architecture
• Identify opportunities for optimization and consolidation
• Collaboration with data team on decomposition of business logic and data transformation patterns

Requirements:

• US Citizen or GC Holders only
• 7-15 years experience
• Primary Skills: AWS DMS (Amazon Web Services Database Migration Service & implementing CDC), AWS Glue, Kafka, or SNS/SQS, Python / PySpark, Data lake, Cloudwatch, Cloudtrail, SNS/SQS, DB design and SQL
• Secondary Skills: AWS IAM, EKS
• Develop Services to enable data ingestion from and synchronization with system which exposes required data access mechanisms ensuring near-real-time updates
• Ingest data from multiple sources using the python and any other ETL tools
• Design and implement an event-driven architecture using AWS EventBridge, Kafka, or SNS/SQS for real-time data streaming
• Design, implement, and maintain scalable data pipelines that integrate both on-prem and AWS cloud environments
• Develop efficient Python scripts and applications using libraries like pandas, NumPy, etc., to handle and process large datasets
• Work with various NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB) to support high-performance data storage and retrieval
• Develop and deploy applications in a cloud-native architecture, leveraging modern cloud technologies for scalability and resilience
• Continuously monitor data workflows and systems, troubleshoot issues, and optimize performance for reliability and scalability
• Transition existing pipeline to MSSQL server
• Collaborate with the business application owner on the existing data architecture, including data ingestion, data pipelines, business logic, data consumption patterns, and analytics requirements
• Design and document the target data architecture, pipelines, processing and analytics architecture
• Identify opportunities for optimization and consolidation
• Collaboration with data team on decomposition of business logic and data transformation patterns