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Mid-level metro Data Engineer role with common AWS/Snowflake stack drives high applicant competition.
Cloud/data platform skills transferable, but Snowflake and regulated-industry experience moderately bias fit.
Explicit 4+ years plus mandatory AWS, Snowflake, Airflow, dbt and Terraform skills create high shortlisting strictness.
Build and maintain scalable and reliable data platforms and pipelines that support analytics and data products across the company.
Manage and optimize AWS infrastructure components including storage, IAM, compute, and orchestration services using Terraform and best practices.
Implement data quality checks, monitoring, lineage, and contribute to governance, access control, and cost optimization within AWS and Snowflake environments.
Minimum 4 years of experience in Data Platform Engineering.
Hands-on experience with AWS core services such as S3, IAM, and compute services.
Proficiency in SQL and Python for data transformation and pipeline development.
Experience working with cloud data warehouses like Snowflake and orchestration tools such as Airflow.
Experienced in building and maintaining data infrastructure using AWS and Snowflake within production environments.
Comfortable working in agile, cross-functional teams alongside senior engineers and data scientists.
Knowledgeable in data modeling fundamentals, data governance, and familiar with orchestration and ETL/ELT workflows using Airflow, dbt, and similar tools.