Data Analyst II

Responsibilities

• Collect, analyze, and interpret data to support business performance, portfolio management, and strategic decision-making within Fleet Solutions.
• Leverage advanced analytical techniques to identify trends, mitigate operational and financial risks, improve data quality, and uncover opportunities to enhance fleet utilization, vehicle lifecycle management, customer experience, and profitability.
• Partner closely with cross-functional teams, including Fleet Operations, Servicing, Finance, Sales, Customer Experience, and IT, to develop scalable data solutions, automate reporting processes, and deliver actionable business intelligence.
• Transform complex data into meaningful insights through dashboards, visualizations, and performance reporting that support both day-to-day operations and long-term strategic initiatives.
• Contribute to forecasting, predictive modeling, and scenario analysis efforts related to vehicle demand, maintenance trends, asset utilization, remarketing performance, and operational efficiency.
• Serve as a trusted business partner, providing analytical expertise and recommendations that drive informed decisions, support continuous improvement, and help achieve Fleet Solutions' operational and financial objectives.
• Develop, maintain, and optimize reports, dashboards, and analytical solutions that provide actionable business insights and support operational and strategic decision-making.
• Partner with business stakeholders, IT, and cross-functional teams to understand business requirements, translate them into analytical solutions, and deliver high-quality reporting products.
• Perform complex data analysis using multiple structured and unstructured data sources to identify trends, risks, opportunities, and process improvement recommendations.
• Validate data accuracy, investigate data quality issues, and collaborate with technical teams to resolve inconsistencies while improving long-term data integrity.
• Create and maintain meaningful business metrics, KPIs, and documentation to support portfolio performance monitoring and operational reporting.
• Present analytical findings and recommendations to business partners and leadership using clear visualizations and concise business storytelling.
• Contribute to the design, enhancement, and automation of reporting processes to improve efficiency, scalability, and data accessibility.
• Provide guidance and knowledge sharing to junior analysts while promoting analytics best practices, documentation standards, and continuous improvement.

Qualifications

• Leverage Power BI and Databricks to build, maintain, and optimize dashboards and reports that clearly communicate business performance, trends, risks, and opportunities to operational and senior leadership audiences.
• Use Databricks to explore, query, transform, and validate large datasets from multiple sources, producing reliable analytical datasets for reporting and decision support.
• Write and troubleshoot SQL to extract, join, aggregate, and reconcile complex data while ensuring results are accurate, complete, and aligned with defined business rules.
• Develop effective Power BI data models, including relationships, calculated columns, measures, and reusable DAX logic that supports consistent and scalable reporting.
• Translate business questions into clearly defined metrics, KPIs, analytical requirements, and reporting solutions, challenging vague or incomplete requests when necessary.
• Apply data visualization and dashboard design best practices to create reports that are intuitive, focused, and actionable rather than simply displaying available data.
• Investigate data discrepancies by tracing issues through source systems, Databricks datasets, transformation logic, and Power BI models, then partner with IT and business teams to resolve root causes.
• Analyze portfolio and operational data to identify meaningful trends, performance drivers, emerging risks, and improvement opportunities, then convert findings into practical recommendations.
• Validate reports and analytical outputs through data reconciliation, reasonableness testing, peer review, and documented quality-control processes before delivery to stakeholders.
• Communicate complex analytical findings in clear business language through written summaries, presentations, and stakeholder discussions, tailoring the level of detail to the audience.
• Manage multiple reporting and analytical priorities by clarifying scope, estimating effort, documenting dependencies, and communicating risks or delays before deadlines are missed.
• Create and maintain documentation for business definitions, data sources, transformation logic, Power BI measures, report functionality, and recurring processes so solutions can be supported and reused by others.
• Partner effectively with business stakeholders, IT teams, data engineers, and other analysts to move work from initial request through requirements, development, testing, implementation, and ongoing support.
• Demonstrate working knowledge of consumer finance, lending, leasing, portfolio performance, or related financial-services concepts, and apply that knowledge when interpreting data and evaluating business impact.
• Support less experienced analysts by reviewing work, sharing Power BI and Databricks best practices, explaining analytical approaches, and helping troubleshoot data or reporting issues.
• Work effectively in a hybrid work environment, with 2 days per week in the office.