Contribute to engineering communities, improve internal libraries and utilities, and evaluate emerging technologies where appropriate
Leverages enterprise-authorized AI-assisted software development tools to improve code quality, delivery speed, and productivity, while validating outputs through peer review, automated testing, and secure coding standards
Applies knowledge of tools within the Software Development Life Cycle toolchain, Agile methodology and automation capabilities, to improve delivery speed and the value realized by automation
Required qualifications, capabilities, and skills
5+ years of experience with formal training or certification on software engineering concepts.
Hands-on experience in system design, application development, testing, and operational stability in production environments
Full stack development experience with Spring, Java, Python, Hibernate, Spark/PySpark, AWS cloud technologies, and Databricks
Experience with relational databases and SQL; familiarity with NoSQL databases and data modeling concepts
Ability to learn other coding languages and technologies as needed, with enthusiasm for continuous growth in both technical aptitude and business understanding
Knowledge across the data lifecycle including ingestion, validation, transformation, storage, governance and lineage considerations, and consumption patterns
Ability to develop, debug, and maintain code in large enterprise environments with established controls and standards
Familiarity with continuous integration and delivery, application resiliency, security best practices, and observability and monitoring
Hands-on experience using enterprise-authorized AI-assisted software development tools with demonstrated ability to critically evaluate and validate AI-generated outputs
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations
Preferred qualifications, capabilities, and skills
AWS Solutions Architect/Developer or advanced-level certification.
Proficiency across the data management lifecycle.
Skilled in resolving code issues and proficient in Git for managing repositories and team collaboration.
