Analytics Engineer (Operations Analytics & Insights)

📋 Description

• • Lendable is at the forefront of revolutionizing consumer finance, aiming to build the world's most advanced technology for credit access and savings. As a rapidly growing fintech unicorn, we are seeking a highly skilled and motivated Analytics Engineer to join our dynamic team. This pivotal role will be instrumental in shaping and enhancing the data infrastructure and analytical capabilities that underpin our critical Operations functions, including Customer Service, Financial Support, Fraud, FinCrime, Complaints, and Quality Assurance.
• • This position is uniquely positioned at the nexus of data engineering, advanced analytics, and operational intelligence. You will be responsible for architecting and implementing robust data models that serve as the foundation for comprehensive operational reporting. Furthermore, you will empower our operational teams by facilitating deeper insights through the strategic application of AI-assisted analytics, sophisticated Python-based analyses, and intuitive self-serve data tools. The overarching objective is to transcend the limitations of traditional, static reporting, thereby fostering a culture of faster, more agile, and scalable decision-making across all operational domains.
• • **Build the Operational Data Layer:** Your primary responsibility will involve the meticulous design, development, and ongoing maintenance of scalable DBT models and SQL pipelines. These pipelines will be crucial for transforming raw operational data from disparate sources into a clean, reliable, and unified analytics layer. You will be tasked with establishing unambiguous metric definitions and standardized data models, ensuring that operational teams can confidently and consistently leverage the same trusted datasets for a multitude of analyses. A key deliverable will be the creation of a singular operational analytics layer that seamlessly integrates data from a diverse array of systems, including customer support platforms, sophisticated risk management systems, quality assurance tooling, and payment processing gateways.
• • **Enable Self-Serve Analytics:** A significant aspect of this role will focus on designing and implementing systems that empower our Operations teams to conduct independent data exploration without the need for constant reliance on manual reporting processes. You will leverage cutting-edge AI-assisted analytics tools, such as Claude or similar Large Language Model (LLM) workflows, to enable teams to query data, generate actionable insights, and explore emerging trends with unprecedented efficiency. Additionally, you will develop and deploy internal tooling and streamlined workflows that significantly enhance the accessibility, comprehensibility, and analytical utility of operational data for all users.
• • **Analytical Deep Dives & Insight Generation:** Beyond routine reporting, you will delve into complex operational datasets to proactively identify inefficiencies, uncover critical behavioral trends, and pinpoint opportunities for significant improvement. Utilizing your expertise in Python and SQL, you will conduct in-depth analyses, creating clear, compelling visualizations that effectively communicate intricate operational dynamics to stakeholders. Your analytical output will include structured investigations into key areas such as Service Level Agreement (SLA) performance and identification of operational bottlenecks, emerging fraud and financial crime trends, optimization of customer support efficiency, patterns in customer complaints and vulnerability identification, and detailed assessments of agent productivity and Quality Assurance (QA) performance.
• • **Data Quality & Integrity:** Ensuring the accuracy, reliability, and scalability of all data pipelines and analytical models will be paramount. You will proactively identify and address any data discrepancies or gaps, continuously enhancing the robustness and resilience of our operational data pipelines. Implementing rigorous processes for maintaining consistent metric definitions and employing version-controlled analytics logic will be essential to uphold data integrity.
• • **Team Development:** This role offers a unique opportunity to mentor and guide junior analysts, imparting best practices in SQL modeling, analytical thinking, data modeling techniques, and effective insight generation. You will play a key role in developing scalable workflows and processes that will enable the Operations Analytics function to grow and mature efficiently as the company expands.
• • **Stakeholder Engagement:** You will serve as a critical analytics partner to Operations leadership, including the Chief Operating Officer (COO) and other senior stakeholders. Your ability to translate complex operational challenges and questions into well-defined data models, insightful analyses, and actionable recommendations will be crucial for driving informed decision-making. Proactively identifying and championing opportunities where data and analytics can significantly enhance operational performance will be a core function of this role.