• Lead the design and implementation of complex cloud infrastructure and services. • Define and enforce cloud-native architecture standards and best practices. • Collaborate with cross-functional teams to align cloud-native solutions with business objectives. • Mentor and guide engineers across multiple teams, fostering professional growth. • Evaluate emerging technologies and recommend adoption strategies. • Ensure security, scalability, and reliability of cloud systems. • Contribute to strategic planning and roadmap development for critical business initiatives.

• End to end ownership of our data warehousing infrastructure, its KPIs and its SLAs. • Design, build, and optimize large-scale, high-performance data pipelines to support analytics, product insights, and operational workflows. • Architect and evolve Sezzle’s data ecosystem, driving improvements in reliability, scalability, and efficiency. • Help Sezzle evolve our data systems beyond the current scale and stack with whatever tooling is necessary to handle processing high volumes of events and performing complex ETL. • Lead development of ETL/ELT workflows on our current tooling using Redshift, DBT, AWS DMS, and related modern data tooling. • Partner with cross-functional teams (engineering, analytics, product, finance, risk) to gather or adapt requirements and deliver robust, high-quality datasets. • Evaluate and integrate new technologies, guiding the evolution of Sezzle’s data stack and infrastructure. • Optimize Redshift and warehouse performance, including query tuning, modeling improvements, and cost management.

• Design and develop scalable and resilient frontend solutions using Appsmith, React, etc. • Design and develop scalable and resilient backend solutions using Java and Spring Boot. • Ensure code quality with a focus on maintainability and performance. • Support dissemination of software engineering best practices, including TDD, BDD, DDD and Clean Code. • Perform code reviews and optimizations. • Collaborate with business areas to translate complex rules into efficient implementations. • Promote technical knowledge sharing and provide support to development teams. • Ensure technical documentation for projects and the security of applications.

• Rapidly prototype and iterate on AI-driven insurance products and experimental features • Own end-to-end delivery of prototypes and MVPs in a scrappy, fast-paced labs environment • Turn ambiguous product ideas into working demos by collaborating with product, solution architects, and domain experts • Leverage AI tools (LLMs, copilots, code generators) to accelerate development and explore novel approaches • Build full-stack applications with usable UIs, robust APIs, and integrations with third-party services • Make pragmatic tradeoff decisions between speed and maintainability, knowing when prototypes need hardening • Provision and manage cloud infrastructure (GCP preferred) to support rapid experimentation • Communicate clearly about technical risks, feasibility, and what's realistically achievable in short timeframes • Collaborate across functions with limited hand-holding, bringing ideas to life with minimal direction • Help define what "production-ready" looks like when prototypes transition to the core platform