Responsibilities Design, develop, and maintain ETL/ELT data pipelines in an AWS environment Implement batch and incremental data processing workflows Build and maintain Change Data Capture (CDC) solutions using AWS DMS and Kafka Develop data transformations in dbt with a strong focus on data quality and consistency Deploy and manage cloud-based data infrastructure on AWS Configure, maintain, and optimize Snowflake data warehouse environments Implement Infrastructure as Code using Terraform Work with relational databases including PostgreSQL, MySQL, and MS SQL Server Design and manage data models for analytical and reporting use cases Monitor data pipelines and troubleshoot failures or data quality issues Ensure data security, manage secrets, and enforce access controls Contribute to architectural decisions and the evolution of the data platform Requirements Minimum 4 years of experience in a Data Engineer role Strong proficiency in Python and SQL Hands-on experience with AWS services, particularly AWS Glue and AWS DMS Experience with Snowflake and dbt, including performance optimization Working knowledge of relational databases (PostgreSQL, MySQL, MS SQL Server) Experience with real-time and streaming data processing using Kafka Proficiency in Terraform and Infrastructure as Code practices Solid experience in building ETL/ELT pipelines and CDC-based integrations Knowledge of data modeling and data warehouse design principles Experience with batch and incremental processing (e.g. SCD) Familiarity with GraphQL APIs Experience using AWS Secrets Manager Understanding of monitoring, data governance, and data security best practices