Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
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 using Java, Kafka, AWS or other cloud technologies like Azure/GCP
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.
Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Streaming & Event-Driven: Apache Kafka, event-driven architecture, messaging patterns (pub/sub), schema management
Preferred qualifications, capabilities, and skills
Strong soft skills, including presentation, negotiation, mentoring, stakeholder management, problem-solving, analytical, and communication skills.
Data Processing: Apache Spark, Apache Flink (stream processing)
AWS certification.