Design, develop, and maintain scalable ETL/ELT pipelines for cloud-based data platforms.
Build and support data integrations between Google Analytics and AWS environments.
Work with GCP data sources, including user and CRM data, and process/analyze data using BigQuery.
Design and maintain AWS data pipelines using Amazon Redshift, Amazon S3, and AWS Glue.
Develop data ingestion, transformation, and loading processes for Redshift-based data warehouses.
Implement and maintain DynamoDB backup, restore, and data extraction processes.
Build reliable data flows between S3, Glue, DynamoDB, and Redshift.
Optimize SQL queries, data models, ETL jobs, and Redshift performance for large datasets.
Implement data quality checks, monitoring, logging, and error-handling mechanisms across data pipelines.
Troubleshoot data pipeline failures, data inconsistencies, and performance issues.
Ensure data security, integrity, availability, and appropriate access controls across AWS environment
Collaborate with analytics, CRM, application, and business teams to understand data requirements and deliver reliable datasets for downstream consumption.
Maintain technical documentation for data pipelines, transformations, data mappings, and operational procedures.
