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High: Tier-1 brand, popular Software Engineer title, and mid-level (3+ years) experience amplify applicant competition.
Medium: core data engineering skills transfer across industries, but enterprise banking systems increase domain specificity.
High: explicit 3+ years and numerous mandatory AWS, PySpark, ETL, RDMS, and IaC skill requirements.
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Design, develop, and troubleshoot secure, scalable software solutions for data ingestion and processing on AWS cloud, including Glue, Lambda, S3, and Aurora databases.
Produce architecture and design artifacts ensuring software meets design constraints and operational stability in a large corporate environment.
Utilize enterprise-authorized AI-assisted software development tools for code creation, testing, and documentation, ensuring validation and secure coding standards.
3+ years of experience developing data ingestion solutions on AWS cloud using services like Glue, S3, Lambda, Event Bridge, Aurora MySQL/PostgreSQL, and PySpark.
Hands-on experience with software development, system design, testing, and operational stability in corporate settings.
Proficient in SQL, PL/SQL, RDMS systems like Oracle, IAM & KMS services, and infrastructure as code tools like Terraform or Cloud Formation.
Experience using enterprise-authorized AI-assisted development tools and ability to validate AI-generated code outputs.
Experienced in designing and building cloud-native data engineering solutions leveraging AWS services and Hadoop ecosystem tools like EMR, PySpark.
Comfortable working with AI coding tools responsibly and integrating them into development workflows for improved quality and productivity.
Familiarity with CI/CD in AWS environments and practical knowledge of security and resiliency best practices in large-scale software systems.