ResponsibilitiesDesign, develop, and maintain ETL/ELT data pipelines in an AWS environmentImplement batch and incremental data processing workflowsBuild and maintain Change Data Capture (CDC) solutions using AWS DMS and KafkaDevelop data transformations in dbt with a strong focus on data quality and consistencyDeploy and manage cloud-based data infrastructure on AWSConfigure, maintain, and optimize Snowflake data warehouse environmentsImplement Infrastructure as Code using TerraformWork with relational databases including PostgreSQL, MySQL, and MS SQL ServerDesign and manage data models for analytical and reporting use casesMonitor data pipelines and troubleshoot failures or data quality issuesEnsure data security, manage secrets, and enforce access controlsContribute to architectural decisions and the evolution of the data platformRequirementsMinimum 4 years of experience in a Data Engineer roleStrong proficiency in Python and SQLHands-on experience with AWS services, particularly AWS Glue and AWS DMSExperience with Snowflake and dbt, including performance optimizationWorking knowledge of relational databases (PostgreSQL, MySQL, MS SQL Server)Experience with real-time and streaming data processing using KafkaProficiency in Terraform and Infrastructure as Code practicesSolid experience in building ETL/ELT pipelines and CDC-based integrationsKnowledge of data modeling and data warehouse design principlesExperience with batch and incremental processing (e.g. SCD)Familiarity with GraphQL APIsExperience using AWS Secrets ManagerUnderstanding of monitoring, data governance, and data security best practices