Analytics Engineer, Credit Risk
About The Position
KOHO is looking for an Analytics Engineer, Credit Risk, to build and scale robust reporting pipelines that power complex credit reporting. In close collaboration with the Credit Team, you'll partner with Payment Operations, Tech, Security, Risk, and Finance teams, as well as fellow Analytics Engineers, on multi-month builds, ensuring our data infrastructure keeps pace with ambitious credit product initiatives. This is a new role bridging analytics engineering excellence with credit data transformation needs. You'll own the technical backbone that enables funds to be accurately processed and reported internally and to financial authorities.
Requirements
- 3+ years of experience in analytics engineering, data engineering, or similar data roles
- Advanced DBT expertise: Comfortable with complex DBT projects, various materializations, such as incremental, table, view, etc. Familiar with snapshots, variables, macros, and Jinja.
- Strong SQL skills with a focus on query optimization and performance
- Experience with modern data stack: DBT Core and/orDBT Cloud, Git. A plus if experience with Redshift.
- Collaborative mindset: You thrive working alongside analysts, PMs, and engineers to translate business requirements into technical solutions
- Strong communicator: You adapt communication to different audiences and connect technical work to reporting outcomes
- Proactive problem-solver: You identify opportunities for improvement and take initiative without waiting to be asked
- AI-curious: Experience or strong interest in leveraging AI tools for development workflows. Strong foundations of AI-assisted development are a plus.
Nice To Haves
- Experience in fintech, credit, and/or banking environments
- Experience with highly-regulated domains
Responsibilities
- Lead complex financial pipeline builds: Design and develop scalable data pipelines supporting banking processes, from scoping through delivery
- Collaborate cross-functionally: Partner with Credit, Payment Operations, Tech, Security, Risk, and Finance teams to define data requirements
- Build credit reporting infrastructure: Create reliable, performant operational data models that power internal and external reporting, audits, and money movements.
- Design scalable data models: Apply modelling frameworks (one big table, entity tables, event streams, Kimball) tailored to credit reporting use cases
- Optimize and monitor: Maintain pipeline health, optimize query performance, and implement data quality monitoring
- Enable the team: Document solutions, establish best practices, and help upskill fellow Analytics Engineers and Analysts
- Integrate cross-functional data: Work across domain boundaries to unify financial data into cohesive reporting structures
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
