Note: The job is a remote job and is open to candidates in USA. Aqua Finance, Inc. is seeking a Senior Credit Analytics Engineer to build and maintain the analytical data foundation supporting lending and credit operations. The role develops scalable data models, reusable SQL assets, transformation workflows, reporting solutions, and trusted analytical data products in collaboration with Data Engineering, IT, Operations, analysts, and business stakeholders.
Responsibilities
- Design, develop, and maintain analytics-ready datasets supporting underwriting, credit risk, pricing, originations, collections, dealer oversight, performance, and portfolio analytics
- Own and evolve the analytical data layer by developing reusable SQL objects, dimensional models, data marts, and curated datasets that enable consistent analysis and decision-making
- Build and maintain scalable, reliable data transformation workflows using SQL, Python, dbt, Git, and Snowflake-native scheduling and automation capabilities
- Simplify, consolidate, integrate, and reconcile data from lending and operational systems into trusted, business-facing analytical data products
- Partner with analysts and business stakeholders to convert recurring or one-time analytical needs into reusable data products and standardized business logic that reduce duplicate effort and accelerate time-to-insight
- Establish and promote reporting and business intelligence best practices, including consistent metrics, reusable datasets, semantic models, documentation, organization, and quality controls
- Develop, maintain, and share ownership of reporting solutions using Power BI, Sigma, or comparable tools while enabling analysts to build and support reports efficiently
- Design analytical solutions that balance speed, flexibility, performance, maintainability, and alignment with longer-term data architecture
- Collaborate with the Data Engineering, IT, and Operations to align analytical solutions with enterprise standards, system capabilities, and business processes
- Implement automated testing, validation, monitoring, and documentation to ensure analytical data assets are accurate, reliable, transparent, and trusted
Skills
- Bachelor's degree in Computer Science, Information Systems, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field, or commensurate work experience required
- 5 years of experience in analytics engineering, data engineering, business intelligence, or advanced analytics required
- Advanced SQL proficiency and experience with Python, dbt, and Git required
- Experience developing, validating, reconciling, and troubleshooting complex analytical datasets across multiple systems
- Experience designing analytics-ready datasets required
- Strong communication, analytical, problem-solving, and organizational skills required
- Snowflake experience preferred
- Experience supporting reporting solutions in Power BI, Sigma, or a comparable platform preferred
- Banking, consumer lending, financial services, fintech, credit risk, or collections experience preferred
Company Overview