We are seeking a skilled and proactive Data Engineer (Mid or Senior) to join our growing data team. In this role, you will design, build, and maintain modern data pipelines and architecture in a cloud-native environment using AWS, Databricks, Python, and dbt. You’ll work closely with analysts, data scientists, and business stakeholders to ensure clean, scalable, and reliable data delivery across the organization. 

• Design, develop, and optimize ETL/ELT pipelines using Databricks and dbt 
• Build and manage data models, data lakes, and data warehouses on AWS 
• Write efficient and scalable code in Python to process large datasets 
• Collaborate with cross-functional teams to understand data needs and deliver solutions 
• Ensure data quality, observability, and performance across the entire pipeline 
• Support continuous integration and deployment of data workflows 
• Implement data governance, security, and compliance best practices 

• Solid experience as a Data Engineer (2+ years for mid, 4+ for senior level) 
• Strong hands-on experience with AWS data services (e.g., S3, Glue, Redshift, Lambda) 
• Proficiency in Python for data engineering tasks 
• Practical knowledge of Databricks and the Spark ecosystem 
• Experience with dbt (Data Build Tool) for data transformation and modeling 
• Familiarity with modern version control and CI/CD workflows (e.g., Git, GitHub Actions, Jenkins) 

• Knowledge of data orchestration tools (e.g., Airflow, Prefect) 
• Experience with data quality tools and observability frameworks 
• Exposure to infrastructure as code (e.g., Terraform, CloudFormation) 
• Experience working in Agile/Scrum environments