Software Engineer III - Python/ AWS/PySpark/Glue

Job Responsibilities: Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Contributes to software engineering communities of practice and events that explore new and emerging technologies Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Detects, troubleshoots and resolves production issues in an enterprise multi-environment settings using advanced observability tools Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 3+ years applied experience Hands-on practical experience in system design, application development, testing, and operational stability Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. Proficient in coding in one or more languages – Python, Java Proficient in private and public Cloud hosted Platform - Pivotal Cloud, AWS. In-depth knowledge is a must for AWS ECS, S3, SQS, SNS, Lambda, Glue, PySpark, CloudWatchExperienced in SRE and Observability tools - Splunk, Dynatrace and Datadog Proficient in Oracle, DB2 and AW Aurora Postgress Database. Hands on experience writing SQL is a must; Hands on experience in Software Development tools and CI/CD tools - Jenkins, Spinnaker, IntelliJ, Bitbucket Hands on experience in IAC – Terraform; Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)Preferred qualifications, capabilities, and skills Overall knowledge of the Software Development Life Cycle Familiarity with modern front-end technologies Experience in Data Pipeline design and development Experience in Cloud migration projects