Data Engineering & Analytics, Credit Review

BankUnited is a financial institution seeking a Data Engineer to support the Credit Review function. This role involves designing, maintaining, and enhancing the data environment for credit risk analytics and reporting, requiring technical skills in SQL, Python, and AWS, along with strong analytical judgment.

Responsibilities:

• Troubleshoot, maintain and enhance existing data pipelines, queries, and scripts supporting Credit Review's AWS-based data environment
• Write and optimize SQL and Python code for data extraction, transformation, and analysis
• Support data validation, documentation, and change control to ensure data quality and reproducibility
• Reconcile quarterly department reporting with other Bank sources of reporting to ensure alignment and to flag and escalate where disconnects exist
• Partner with internal stakeholders to deliver ad hoc and recurring analytics to support credit risk identification and monitoring
• Create, refine, and maintain dashboards and reports used to inform senior management and the Board
• Assist in developing new data models and tools to enhance Credit Review's monitoring coverage and automation
• Collaborate with technology partners to ensure alignment with enterprise data architecture, security, and governance standards
• Participate in periodic internal and regulatory exams by preparing and validating datasets used for testing and analytics
• Stay current on emerging data tools and techniques that can improve Credit Review's analytical efficiency and insight generation
• Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.)
• Adheres to Bank policies and procedures and completes required training
• Identifies and reports suspicious activity
• Supervises function, projects or services and/or one or more employees, as applicable
• Carries out supervisory responsibilities in accordance with the organization's policies and applicable laws
• Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance coaching; rewarding and disciplining employees; addressing complaints and resolving problems

Requirements:

• Bachelor's Degree in a quantitative or technical field (eg, Computer Science, Mathematics, Engineering, Economics, or Statistics) required
• Minimum 3 years of relevant experience in data engineering, data analytics, or quantitative analysis - preferably within financial services, banking, or risk management required
• Hands-on experience with AWS data tools (eg, S3, Glue, Lambda, Step Functions, Athena, Redshift) required
• Strong command of SQL and Python; ability to read, maintain, and enhance production code required
• Knowledge of data analytics practices and concepts (CAAT, trend analysis, data visualization, regression analysis)
• Ability to perform challenging data queries, data mining, reconcile data, analyze results, and form conclusions for Credit Review and senior management
• Knowledge of commercial and retail loan portfolios, reporting, and analysis techniques
• Collaborative and team-oriented, with an appreciation for data governance, data quality and risk management principles
• Detail-oriented, organized, and self-directed with a strong sense of ownership
• Excellent written and verbal communication skills, including the ability to explain technical concepts to non-technical audiences
• Ability to work independently and prioritize tasks in a fast-paced environment
• Master's Degree preferred
• Familiarity with version control (GitHub) and cloud development workflows preferred
• Experience with visualization tools (especially QuickSight) a plus preferred
• Exposure to credit or financial risk models (eg, PD/LGD, CECL, stress testing) is a differentiator preferred
• Experience developing or supporting AI/ML or automation tools is a strong plus preferred