Description

Job Description

Roles & Responsibilities
We are seeking a highly skilled Senior AWS Data Engineer with expertise in Fivetran, AWS Glue, Python, SQL, and cloud-native data engineering. The ideal candidate will be responsible for building scalable data ingestion and transformation frameworks, enabling analytics, data products, and AI-driven initiatives across the enterprise. Exposure to Amazon Bedrock and modern GenAI architectures is highly desirable.

Key Responsibilities

• Design, develop, and maintain enterprise-scale data pipelines using AWS services.
• Implement and manage data ingestion frameworks using Fivetran.
• Develop ETL/ELT workflows using AWS Glue and PySpark.
• Build and optimize data lake solutions on AWS.
• Perform source-to-target mapping and support data migration initiatives.
• Implement data quality, validation, reconciliation, and monitoring frameworks.
• Develop reusable pipeline patterns and automation frameworks.
• Collaborate with architects, business stakeholders, and analytics teams to deliver trusted data products.
• Support AI and GenAI use cases by preparing and managing high-quality datasets.
• Follow DataOps, CI/CD, governance, and security best practices.

AWS Technologies

• Amazon S3
• AWS Glue
• Lambda
• IAM
• CloudWatch
• EventBridge
• Step Functions

Data Engineering

• ETL / ELT Development
• Data Warehousing
• Data Lake Architecture
• Source-to-Target Mapping
• Data Quality Frameworks
• Pipeline Automation
• Performance Optimization

DevOps / DataOps

• Git
• CI/CD Pipelines
• Agile Delivery
• Infrastructure Automation

Preferred Skills

• Amazon Bedrock
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Snowflake
• dbt
• Apache Airflow
• Data Catalog & Governance
• Amazon Textract
• AI/ML Integration and Data Preparation

Key Skills

Education

Any Graduate