Senior Credit Analytics Engineer: Scalable Lending Data

Aqua Finance, Inc.; Northern (KY); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Aqua Finance, Inc. seeks a Senior Credit Analytics Engineer to design and maintain analytics-ready datasets for underwriting, pricing, originations, and portfolio analytics.

You will build scalable data workflows and reusable SQL assets while partnering with Data Engineering, IT, and Operations to ensure data quality and governance. Responsibilities include developing reporting assets with Power BI or Sigma, establishing best practices, and documenting data products for analysts and leaders.

Qualifications

• Bachelor's degree in a quantitative field or commensurate work experience.
• 5 years of analytics engineering/data engineering/BI/advanced analytics experience required.
• Advanced SQL proficiency; experience with Python, dbt, and Git required.
• Experience building analytics-ready datasets across multiple systems.
• Snowflake experience preferred; Power BI or Sigma reporting experience preferred.

Responsibilities

• Design, develop, and maintain analytics-ready datasets supporting underwriting, credit risk, pricing, originations, collections, and portfolio analytics.
• Build reusable SQL objects, dimensional models, data marts, and curated datasets to enable consistent analysis.
• Develop scalable data transformation workflows using SQL, Python, dbt, Git, and Snowflake scheduling/automation.
• Produce trusted reporting assets and documentation; promote BI best practices and standardized logic.
• Collaborate with analysts and stakeholders to translate needs into reusable data products and quality controls.

Skills

SQL

Python

dbt

Git

Snowflake

Education

Bachelor's degree in a quantitative field

Tools

Power BI

Sigma

Job description

Aqua Finance, Inc. seeks a Senior Credit Analytics Engineer to design and maintain analytics-ready datasets for underwriting, pricing, originations, and portfolio analytics.

You will build scalable data workflows and reusable SQL assets while partnering with Data Engineering, IT, and Operations to ensure data quality and governance. Responsibilities include developing reporting assets with Power BI or Sigma, establishing best practices, and documenting data products for analysts and leaders.