Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 5+ years of experience in Data Engineering or related roles.
• Hands-on experience with Snowflake, DBT, enterprise ETL/ELT tools, scheduling/orchestration tools (Airflow, Control-M, Autosys, etc.), AWS S3, AWS Glue, and AWS Lambda.
• Strong understanding of SQL and data warehousing concepts.
• Knowledge of data modeling, data governance, and data quality best practices.
• Strong analytical and problem-solving capabilities.
• Excellent verbal and written communication skills.

Responsibilities

• Design, develop, and maintain robust and scalable data pipelines for ingestion, transformation, and loading.
• Build and optimize data models and transformation workflows using DBT.
• Develop and support ETL/ELT processes with enterprise ETL tools.
• Implement and manage data warehousing solutions using Snowflake.
• Utilize AWS S3 for data storage and lake architectures.
• Create and maintain data integration workflows using AWS Glue.
• Design and develop serverless data processing solutions with AWS Lambda.

Benefits

• Opportunity to work with cutting-edge technology in data engineering and cloud computing.
• Collaboration with a dynamic team of data analysts, architects, and stakeholders.
• Professional development opportunities, including potential certifications.
• A chance to work in an Agile environment that promotes innovation.
• Emphasis on data quality and governance, ensuring meaningful contributions to organization.