Jobs at Forward Financing

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical architecture and roadmap for analytics engineering: design semantic/metrics layer, build AI-ready Snowflake data foundation, optimize dbt projects, mentor engineers, partner with Data Science/Engineering, and champion data governance, observability, and production readiness for AI and downstream analytics.

Design, build, and maintain scalable dimensional data models, semantic/metrics layers, and production data pipelines (dbt, Snowflake). Partner with Data Science, Data Engineering, BI, and DevOps to enable AI/ML, real-time analytics, governance, and data quality while mentoring junior engineers and enforcing best practices.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Lead technical architecture and roadmap for analytics engineering, build and govern semantic/metrics layers, optimize dbt and Snowflake performance, mentor engineers, partner with Data Science and Data Engineering to deliver AI-ready data foundations and ensure data quality and governance.

Lead and grow a team of analytics engineers to build an AI-ready, centralized data foundation. Hands-on duties include writing/reviewing SQL and dbt, designing semantic and dimensional data models, driving data quality, observability, testing, and CI/CD, partnering cross-functionally to deliver scalable data products, and recruiting and developing engineering talent.

Design, build, and maintain dimensional data models, semantic layer, and production data transformation pipelines (dbt/Snowflake). Partner with Data Engineering, Data Science, BI, and Product to deliver governed, AI-ready data products, monitor data quality, enable ML features, and coach junior engineers to uphold code and governance standards.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead and scale IT operations for a growing fintech: maintain and upgrade systems, manage day-to-day support and endpoints (Mac/Windows/ChromeOS), define metrics, run large IT projects, manage vendors and office technology, implement security/compliance, expand support coverage, and travel internationally twice yearly.

Support execution of brand, communications, and content programs including social media management, content creation using generative AI, event coordination, partner enablement, PR support, government affairs assistance, and marketing operations. Manage calendars, reporting, vendor coordination, and AI-assisted workflows to amplify Forward Financing's brand and partner programs.

Manage cash forecasting, lead treasury operations, evaluate and implement management systems, and collaborate across departments to enhance cash management.

Lead BI analyst leveraging a modern data stack to deliver dashboards, automated reports, and AI-driven insights. Partner with stakeholders to define data needs, build Tableau visualizations, write complex SQL in Snowflake, and integrate Snowflake Intelligence/Claude to automate workflows and enable self-service analytics across the company.

Drive high-volume outbound re-engagement of paid-in-full merchants to generate new funding opportunities. Use CRM (Salesforce) and auto-dialer tools, analyze performance metrics, mentor junior reps, collaborate with cross-functional teams, pilot beta technologies, and meet strict activity, conversion, and quota targets.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

The Senior Customer Engagement Representative focuses on re-engaging previous clients with a paid in full balance, utilizing high-volume dialing, Salesforce for management, and mentoring junior representatives while optimizing performance metrics for conversion and revenue targets.

Lead end-to-end data science initiatives: design, deploy, and monitor ML/statistical models for credit risk, pricing, collections and fraud. Collaborate cross-functionally to integrate models into production, define model development standards, mentor team members, and maintain scalable ML pipelines and monitoring systems to drive measurable business impact.

Provide high-quality inbound/outbound phone, email, and chat support to customers and partners, meet SLA and KPI targets, handle routing to internal teams, participate in continuous improvement and 1:1 coaching, and maintain a positive, empathetic, customer-focused approach in a fast-paced environment.

The Senior Director of Inside Sales leads a team of over 70, focusing on sales strategy, performance management, and talent development to drive revenue growth in a high-volume, fast-paced fintech environment.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Manage a portfolio of small and medium business customers to grow relationships and identify additional capital solutions. Analyze business and financial histories, own the sales process from approval to close, use data to prioritize opportunities, and meet monthly quota in a fast-paced environment.