• Design, develop, and support complex enterprise integrations using Boomi (iPaaS) within hybrid on‑premise and Microsoft Azure cloud environments. • Develop and maintain data integration workflows leveraging Microsoft SQL Server and Transact‑SQL, including stored procedures, data transformations, and performance optimization for high‑volume transactional systems. • Build, configure, and support Microsoft Azure integration services, including Azure Logic Apps, Integration Accounts, and API-driven workflows for B2B and application integrations. • Design and implement EDI integrations, including mapping, trading partner onboarding, document validation, and secure data exchange. • Develop and enhance integration components using C# / .NET technologies, including custom services, APIs, and middleware components supporting integration flows. • Collaborate with business analysts and stakeholders to translate functional requirements into scalable integration and data solutions. • Perform advanced data analysis and troubleshooting across SQL Server, Boomi, and Azure platforms, ensuring data accuracy, integrity, and system performance. • Optimize integration performance through efficient SQL query design, indexing strategies, and data flow optimization. • Participate in solution architecture design sessions, ensuring alignment with enterprise integration and cloud strategies. • Conduct code reviews and enforce standards for integration design, SQL development, and application code quality. • Develop and maintain technical documentation, including integration architecture diagrams, data flow mapping, and deployment procedures. • Provide Level 2 support and participate in incident resolution for integration, database, and EDI-related issues.

• Act as a technical reference in the architecture of cloud-native distributed systems and microservices • Actively participate in the design, conception, and evolution of high-availability, high-scale platforms focused on real-time financial transaction processing • Collaborate across engineering teams, promoting best practices, architectural consistency, and raising the team's technical level • Make and document architecture decisions clearly, outlining trade-offs, costs, and business impact • Create and evolve infrastructure as code (IaC), ensuring reproducible, secure, and scalable environments • Collaborate with product and business teams, translating requirements into robust technical solutions • Promote a culture of observability, security, and production performance • Adopt and disseminate AI-assisted development practices to increase team velocity and delivery quality

• Act as the squad's technical lead, developing and implementing end-to-end solutions from backend to frontend. • Ensure continuous, agile deliveries that allow the team to validate experiments and iterate quickly while maintaining quality. • Implement scalable solutions that optimize performance on both the frontend and backend. • Collaborate with the Product Manager, Designers, and other stakeholders to align business needs with engineering best practices. • Define and follow coding best practices, including automated tests, code reviews, and secure deployment processes. • Develop integrations with tools and APIs that support data analysis and growth experiments. • Support the team in designing and running experiments and A/B tests, focusing on rapid improvements and continuous learning. • Collaborate with other squads to implement and scale successful initiatives across Astrea.

• Tackle ambiguous, cross-system problems spanning all aspects of fulfillment and servicing • Own large features end to end, from design through deployment, release, and monitoring • Deliver scalable, event-driven, AI-native applications that elevate the customer experience • Collaborate with platform teams to enhance overall system architecture • Own the design, implementation, quality and safety of AI/agentic features in production systems • Mentor other engineers across levels through code review, pairing, design collaboration and coaching • Drive adoption of tooling and practices, including AI developer tooling, and codify the habits that make them effective • Advocate for the proactive investments — refactors, observability, upgrades, technology adoption - that enable continuous improvement • Communicate fluently across product, design, solutions, and ops to align outcomes with business goals