At Sunbit, we're building financial technology that puts people first. By combining intelligent decisioning with a personalized, transparent approach, we help consumers access the payment options that are right for them while empowering merchants to build stronger customer relationships.
Engineering is at the heart of how we make that happen. We build scalable distributed systems, cloud-native services, intelligent data platforms, and AI-powered solutions that enable real-time financial decisions at scale. By leveraging modern engineering practices and integrating AI into both our products and development workflows, we solve complex technical challenges, accelerate innovation, and continuously improve the way we build software. Every service, model, and architectural decision we make directly impacts our products, our customers, and the future of financial technology
As part of our Account Management Data Engineering team, you will not only build scalable data features and pipelines but also directly enable portfolio growth by supporting new business capabilities in the Credit Card and Loan Management business units.
What you'll do
Design and build data solutions that support Sunbit's Credit Card and Loan Management business goals.
Develop advanced data pipelines to support the infrastructure, architecture, and product growth initiatives.
Create ETL/ELT processes and SQL queries to bring data to the data warehouse and other data sources.
Own and evolve data lake pipelines, including maintenance, schema management, and ongoing improvements.
Collaborate with stakeholders across Product, Backend Engineering, and Data Science to align technical work with business outcomes.
Implement new tools and modern development approaches that improve both scalability and business agility.
Ensure adherence to coding best practices and development of reusable code.
Constantly monitor the data platform and make recommendations to enhance architecture, performance, and cost efficiency.
Requirements
B.Sc. in Computer Science, Engineering, or a related field (or equivalent experience).
4+ years of experience as a Data Engineer.
4+ years of Python and SQL experience.
4+ years of experience in data modeling and building scalable ELT/ETL pipelines on Snowflake.
3+ years of experience designing and managing automated data pipelines using Apache Airflow (Python).
DBT experience — required. 3+ years developing scalable, production-grade data models with DBT.
Hands-on experience with cloud environments (AWS preferred) and big data technologies.
Strong troubleshooting and debugging skills in large-scale systems.
Proven experience packaging applications with Docker and utilizing Argo Workflows to automate, execute, and monitor containerized task sequences.
Experience with design patterns and coding best practices.
Proficiency with Git and modern source control.
Basic Linux/Unix system administration skills.
Familiarity with LLM-assisted coding tools.
Nice to have
Experience with NoSQL or large-scale databases.
Experience with microservices architecture.
Familiarity with Airbyte or other modern ETL platforms.
Experience with Apache Spark or Apache Kafka and the broader Data Engineering ecosystem.
Recruitment Fraud Disclaimer
We’ve been made aware of fraudsters impersonating Sunbit employees during the hiring process. Please note that all official communication will come from an @sunbit.com email address, through our applicant tracking platform @sunbit.comeet-notifications.com or directly via LinkedIn. We will never ask for your age, Social Security number, bank account details, payment of any kind, or other unrelated personal information during the application process. Our hiring process always includes interviews, either by phone, zoom, or in person, before any offer is made. If something feels suspicious, please contact us at HR to confirm. We ask that you contact HR only about potential instances of fraud. HR does not reach our recruiting team directly. Your application directly through the posting is the best way to ensure that your candidacy is reviewed by our team. Due to the volume of applications, we will not respond to nor forward emails about your candidacy that are sent to HR directly, and your email about your application will be deleted from our systems.