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Common mid-level data engineer role in a metro with broad ETL/AWS skillset increases competition.
Data engineering skills (SQL, ETL, AWS) are highly transferable across industries, so low sensitivity.
Explicit 5+ years and mandatory ETL/AWS/SQL production experience create high shortlisting strictness.
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End-to-end ownership of designing, developing, optimizing, and supporting enterprise-scale ETL/ELT pipelines and data warehouse solutions.
Develop, optimize, and tune complex SQL queries for high-performance processing of large datasets across relational databases.
Design and maintain AWS cloud data platform pipelines and enable secure, governed, and scalable data access while driving cloud migration and modernization.
5+ years of experience in Data Engineering, ETL Development, or Data Warehousing.
Strong expertise in ETL development and enterprise data warehousing, including dimensional modeling and data integration architecture.
Proficient in complex SQL query development, optimization, and performance tuning on relational databases (e.g., Oracle, SQL Server, PostgreSQL, MySQL, Teradata, DB2).
Exposure to AWS cloud data services and cloud-native data engineering platforms; Bachelor's degree in Computer Science or Information Technology.
Demonstrates proven ability to independently deliver large-scale data engineering solutions from requirement gathering through production support with end-to-end accountability.
Experienced working directly with business stakeholders and cross-functional technical teams in enterprise environments.
Skilled in handling large datasets, performance tuning, and modern cloud-based data platform architectures with AWS services.