Job Summary

Bring your data engineering and modernization expertise to a role where your pipelines, automation solutions, and dashboards directly power small business lending decisions. You’ll join a team that turns complex lending portfolio and pricing data into clear, decision-ready intelligence. Partnering closely with Finance, Risk, Product, and Technology, you’ll help build the automated infrastructure that keeps the financial intelligence function running with speed, precision, and strong governance. If you thrive on replacing manual processes with scalable solutions and take pride in outputs that are both technically sound and business-ready, you’ll find meaningful impact here.

As a Senior Associate in Business Banking Lending Finance, you will own the automation roadmap and build production-grade data pipelines that serve the financial intelligence team. You will design executive dashboards that do not just display data — they tell a story and guide a decision. You will respond rapidly when the team needs a new metric or reporting dimension, scoping, building, testing, and deploying it correctly. You will maintain controls across all automated processes and ensure every output is auditable, traceable, and defensible. Financial literacy in lending is valued; the ability to recognize when an output looks wrong before it reaches a stakeholder is essential.

Job Responsibilities:

• Own and execute the automation roadmap for BB Lending Finance — identifying manual reporting and analytical processes and replacing them with scalable, governed, automated solutions.
• Build and maintain production-grade data pipelines using SQL, Python, and Databricks that ingest, transform, validate, and serve financial data reliably at scale.
• Design and build executive-grade dashboards in Tableau and other visualization tools, applying visual hierarchy, narrative discipline, and audience awareness to guide decisions — not just display data.
• Implement data quality checks, source-to-target validation, data lineage documentation, and business rules so every number on every dashboard is traceable and defensible.
• Respond rapidly to new requirements from the financial intelligence team — scope, build, test, and deploy without sacrificing quality or controls.
• Leverage AI-assisted development tools to accelerate build quality, code documentation, and pipeline efficiency.
• Partner with Technology and Data Engineering teams to integrate financial data across source systems using sound data modeling, dimensional design, and governance practices.
• Identify opportunities to modernize financial operations and management reporting through data centralization and the development of intelligent, automated solutions.

Required qualifications, capabilities, and skills:

• 4+ years of progressive experience in data engineering, analytics engineering, or a related technical field.
• Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field.
• Advanced SQL proficiency — clean, efficient, and readable code.
• Production-level Python for data transformation, pipeline automation, and analytical tooling.
• Hands-on experience with Databricks or an equivalent cloud data platform such as Snowflake, Azure, or AWS.
• Demonstrated mastery of Tableau, Power BI, or equivalent — including data modeling, automated refresh, drill-through design, and a portfolio of dashboards you can defend.
• Data quality and governance experience — validation frameworks, reconciliation processes, source-to-target mapping, and lineage documentation.
• Strong communication skills — able to translate a technical constraint or data quality issue into plain language a finance stakeholder understands and trusts.
• Quality obsession and aesthetic judgment — knows the difference between a dashboard that informs and one that overwhelms, and never confuses the two.
• Strong attention to detail with a well-organized, solutions-oriented approach.

Preferred qualifications, capabilities and skills 

• Experience supporting a financial intelligence, FP&A, or pricing analytics function in a banking or financial services environment.

• Familiarity with lending portfolio analytics, including performance metrics and profitability frameworks.
• Experience with AI-assisted coding tools and exposure to agentic AI concepts, with practical experience applying AI agents to automate multi-step analytical or reporting workflows.
• Experience designing data models for financial reporting.
• Advanced degree in a quantitative field is a plus.