Cloud Data Engineer (AWS)

Responsibilities and Requirements

• Manage and Optimise existing data storage solutions, including databases, data lakes, and warehouses, using AWS services such as Amazon S3, Amazon RDS, Amazon Redshift, and Amazon DynamoDB, along with Databricks' Delta Lake. Integrate Informatica IDMC for metadata management and data cataloging.
• Manage and optimize data pipelines for ingesting, processing, and transforming data using AWS services like AWS Glue, AWS Data Pipeline, and AWS Lambda, Databricks for advanced data processing, and Informatica IDMC for data integration and quality.
• Integrate data from various sources, both internal and external, into AWS and Databricks environments, ensuring data consistency and quality, while leveraging Informatica IDMC for data integration, transformation, and governance.
• Manage ETL (Extract, Transform, Load) processes to cleanse, transform, and enrich data, making it suitable for analytical purposes using Databricks' Spark capabilities and Informatica IDMC for data transformation and quality.
• Monitor and optimize data processing and query performance in both AWS and Databricks environments, making necessary adjustments to meet performance and scalability requirements. Utilize Informatica IDMC for optimizing data workflows.
• Implement security best practices and data encryption methods to protect sensitive data in both AWS and Databricks, while ensuring compliance with data privacy regulations. Employ Informatica IDMC for data governance and compliance.
• Implement automation for routine tasks, such as data ingestion, transformation, and monitoring, using AWS services like AWS Step Functions, AWS Lambda, Databricks Jobs, and Informatica IDMC for workflow automation.