Senior Data Engineer

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.