About this role
Job Description
• Design, develop, and maintain scalable and efficient ETL/ELT pipelines using tools such as AWS Glue, DBT, and Airflow. • Build and automate event-driven data workflows leveraging AWS Lambda, EventBridge, and related services. • Integrate data replication tools like Hevo or Fivetran for seamless ingestion from external systems. • Perform data modeling (dimensional and normalized) to support Tableau team and analytics. • Manage infrastructure as code using Terraform and automate workflows using GitHub Actions. • Optimize and maintain Snowflake data warehouse environments, including performance tuning and data lifecycle management. • Use GitHub Actions to deploy DBT projects, manage data pipelines, and automate testing/monitoring tasks. • Collaborate with analysts, data scientists, and engineering teams to gather requirements and deliver robust data solutions. • Ensure data quality, integrity, and consistency across all systems and processes. • Containerize data workflows using Docker for portability and repeatability. • Productionalizes SQL queries from data analysts into structured dbt models within the silver/gold layer
Requirements
• 4–6 years of experience as a Data Engineer or in a similar role. • Hands-on experience with AWS data services: Glue, Lambda, EventBridge, S3, IAM, Airflow/MWAA • Proficiency in SQL and Python for data manipulation and orchestration. • Snowflake data warehouse design and query optimization • Solid experience with DBT, Apache Airflow, and Snowflake (or other cloud data warehouses). • Experience using GitHub Actions for CI/CD in data workflows. • Familiarity with data replication tools such as Hevo or Fivetran. • Strong understanding of data modeling principles (e.g., star/snowflake schema). • Prior experience in eCommerce, retail, or high-volume transactional data environments. • Infrastructure-as-Code expertise using Terraform. • Experience containerizing pipelines with Docker, ECR and EKS. • Strong problem-solving and communication skills in a collaborative, cross-functional environment.
Job Description
• Design, develop, and maintain scalable and efficient ETL/ELT pipelines using tools such as AWS Glue, DBT, and Airflow. • Build and automate event-driven data workflows leveraging AWS Lambda, EventBridge, and related services. • Integrate data replication tools like Hevo or Fivetran for seamless ingestion from external systems. • Perform data modeling (dimensional and normalized) to support Tableau team and analytics. • Manage infrastructure as code using Terraform and automate workflows using GitHub Actions. • Optimize and maintain Snowflake data warehouse environments, including performance tuning and data lifecycle management. • Use GitHub Actions to deploy DBT projects, manage data pipelines, and automate testing/monitoring tasks. • Collaborate with analysts, data scientists, and engineering teams to gather requirements and deliver robust data solutions. • Ensure data quality, integrity, and consistency across all systems and processes. • Containerize data workflows using Docker for portability and repeatability. • Productionalizes SQL queries from data analysts into structured dbt models within the silver/gold layer
Requirements
• 4–6 years of experience as a Data Engineer or in a similar role. • Hands-on experience with AWS data services: Glue, Lambda, EventBridge, S3, IAM, Airflow/MWAA • Proficiency in SQL and Python for data manipulation and orchestration. • Snowflake data warehouse design and query optimization • Solid experience with DBT, Apache Airflow, and Snowflake (or other cloud data warehouses). • Experience using GitHub Actions for CI/CD in data workflows. • Familiarity with data replication tools such as Hevo or Fivetran. • Strong understanding of data modeling principles (e.g., star/snowflake schema). • Prior experience in eCommerce, retail, or high-volume transactional data environments. • Infrastructure-as-Code expertise using Terraform. • Experience containerizing pipelines with Docker, ECR and EKS. • Strong problem-solving and communication skills in a collaborative, cross-functional environment.
Education: Bachelor’s degree in computer sciences/IT stream. 4–6 years of experience as a Data Engineer or in a similar role.