Understanding of secure coding fundamentals, including input validation, secrets management, access control, and protection of sensitive data.
Strong analytical thinking, troubleshooting, and problem-solving skills, with the ability to learn unfamiliar technologies quickly.
Clear communication and collaboration skills, with the ability to work effectively in Agile delivery teams and manage multiple priorities while maintaining delivery quality.
The Skills that are Good To Have for this Role
Hands-on exposure to building or integrating micro-front-end applications through professional work, internships, academic assignments, open-source contributions, or personal projects.
Experience with Python web frameworks or Node.js service frameworks, without requiring expertise in a specific framework.
Familiarity with additional integration patterns such as GraphQL, asynchronous messaging, event-driven architecture, webhooks, or service-to-service communication.
Exposure to Snowflake or another cloud data warehouse, and to AWS-based application or data services.
Experience with ETL tools, orchestration platforms, or workflow technologies such as Control-M, Informatica, NiFi, or similar solutions.
Familiarity with containerization, cloud deployment, application configuration, automated build pipelines, and observability practices.
Exposure to application and API testing tools, test automation, performance testing, and monitoring or logging platforms.
Understanding of design systems, reusable component libraries, user experience principles, and accessible application design.
Exposure to Power BI, Tableau, or other self-service analytics and embedded analytics platforms.
Familiarity with Alation, Collibra, or enterprise metadata and catalog solutions.
Experience supporting AI/ML or GenAI use cases through application integration, API orchestration, semantic layers, context preparation, or AI-ready datasets.
Exposure to Customer Analytics, Customer Engagement Analytics, Digital Analytics, Behavioral Analytics, Financial Services, Wealth Management, Brokerage, Customer Experience, or Enterprise Analytics environments.
Understanding of customer segmentation, customer profiling, retention, attrition, and customer lifecycle analytics use cases.
