• Maintain and enhance existing data processes to ensure reliability, performance, and scalability • Improve and support Python-based services, as well as develop new ones • Design, implement, and optimize scalable data architecture • Drive improvements in system reliability and performance across all data workflows • Modernize data processes by introducing new tools and technologies • Manage data flow between local storage, AWS, and Snowflake with a focus on performance and cost efficiency • Lead migration of data pipelines and services to Snowflake • Work with and improve the data orchestration layer (Airflow) for stable operation and scalability • Collaborate with cross-functional teams to ensure architectural alignment and adoption of best practices

• May lead small project teams or project phases of larger scope • Works independently with minimal guidance and direction • Impacts a range of customer, operational, project or service activities within own team and related work teams • Contributes to the development of concepts, methods, and techniques • Solves variety of problems of moderately complex or unusual within own area • Applies independent judgement to develop creative and practical solutions based on the analysis of multiple factors • Anticipates and identifies problems and issues • May provide technical direction to others around the completion of short-term work goals • Trains and guides others in work area on technical skills • Networks with senior colleagues in own area of expertise

• 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.