Forward Financing

Role Description As In-House Counsel, you will manage the Company’s arbitration caseload from inception to resolution and assist with various broader legal matters. Reporting to the Senior Managing Counsel, you will collaborate with a dedicated team of legal assistants and partner across departments with internal stakeholders and cross-functional teams. In this role, you will: - Draft and review all Arbitration documents including pleadings, legal briefing, and settlement agreements. - Embrace automation and AI-focused workflows to own a portfolio of 800+ Arbitration matters, following each case from inception to conclusion. Assist in guiding legal strategy. - Prepare all discovery production, engage in discovery conferences and motion practice as needed. - Oversee the preparation and submission of evidentiary documents. - Work to incorporate company-adopted AI tools into work management. - Assist with courtroom litigation or subpoenas involving the Company. - Provide assistance with various other general matters within the legal/account servicing department. - Communicate effectively with customers on escalated accounts and provide succinct updates to senior leadership. Qualifications - 2+ years of experience as an attorney in a busy litigation or arbitration-centered practice. - Admitted to practice law in the Commonwealth of Massachusetts and in good standing. - Demonstrated ability to communicate effectively with senior management, colleagues, and external counsel. - Excellent writing and legal analytic skills. - Self-motivated, organized, and able to work independently. - Effective in a fast-paced environment. - Adaptable. Requirements - Annual Targeted Salary: $131,000 – $164,000 USD - Annual Target Bonus: 10% Benefits - Comprehensive total rewards package, including but not limited to: medical, dental, vision, commuter benefits, a flexible time-off policy, paid parental leave, 401k match for US employees, wellness reimbursement, volunteering days, annual professional development budget, and charitable donation match. - Remote-first company with workplace flexibility.

Forward Financing is a financial technology company based in Boston, Massachusetts with team members throughout the United States, Dominican Republic, and Canada. The company is on a mission to unlock the capital that fuels small businesses across America. Recognized as a Best Place to Work by Built In Boston and certified as a Great Place To Work®, Forward is investing in its employees, technology, and customer experience – with long-term success in mind every step of the way. The Analytics Engineering team at Forward plays a central role in our Data ecosystem, partnering with technical and business stakeholders to convert raw data into trusted, AI-ready insights. Our team builds and optimizes data infrastructure, designs the data models and semantic layer that power Forward's source of truth, and develops the pipelines that fuel business intelligence, advanced analytics, predictive modeling, and the next generation of AI-driven experiences at the company. As a Lead Analytics Engineer, you will be the senior technical voice on the team - setting architectural direction, owning our most complex and cross-cutting initiatives, and raising the bar for everyone around you. You'll partner closely with the Manager of Analytics Engineering to drive Forward's data centralization vision, architect the semantic layer that serves as the company's single source of truth, and build the AI-ready data foundation that powers Snowflake Intelligence, agent-based use cases, and machine learning at Forward. You'll mentor Senior and Analytics Engineers across the team and act as a trusted technical partner to leaders in Data Science, Data Engineering, BI, and Product. In This Role You Will: - Own the technical architecture and roadmap for our most complex Analytics Engineering initiatives - including semantic layer design, source-of-truth consolidation, and the data foundation for AI and agent-based use cases - Architect Forward's semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products - Lead the technical design of the AI-ready data platform - making the modeling, metadata, and governance decisions that make Snowflake Intelligence and other AI/agent capabilities trustworthy, performant, and production-ready - Drive technical excellence across our dbt project: model architecture, materialization and incremental strategies, performance tuning, macros, testing patterns, and CI/CD practices that scale as data volume and team size grow - Set and uphold a high bar for craftsmanship across the team - defining standards for SQL style, modeling patterns, documentation, and data quality, and modeling those standards in your own work - Mentor Senior and Analytics Engineers through hands-on code review, pairing, and design feedback - accelerating their growth into stronger technical contributors - Partner with the Manager of Analytics Engineering on technical strategy, hiring, and roadmap planning - acting as a deputy for technical decisions and unblocking the team on the hardest problems - Lead deep technical partnerships with Data Science, Data Engineering, and Core Technology - owning schema migrations, feature deployments, and streaming pipeline contributions where Analytics Engineering is on the critical path - Evaluate and operationalize high-value third-party data sources and emerging tooling (e.g., Snowflake Cortex, semantic layer frameworks, observability tools) and make recommendations that elevate the platform - Champion data governance and quality at the platform level - including dbt tests, lineage, cataloging, observability, and compliance with security and regulatory standards - so both stakeholders and AI systems can trust the numbers Role Requirements:(Even if you don't check every box, but see yourself contributing, please apply.) - 6+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence, with a track record of leading complex, cross-cutting technical initiatives - 4+ years of hands-on production experience with dbt, including advanced patterns such as incremental strategies, macros, custom tests, and CI/CD design - 3+ years of deep experience with a cloud-based data warehouse (Snowflake strongly preferred), including performance tuning and cost optimization - Expert-level proficiency in SQL and dimensional data modeling, with a portfolio of durable, well-tested models that have served as foundational layers for an organization - Demonstrated experience designing and operating a semantic layer or metrics layer that serves as an organizational source of truth - Proven ability to mentor senior engineers, lead architectural decisions, and influence direction across cross-functional teams - Excellent written and verbal communication skills - able to drive technical alignment with both engineers and non-technical stakeholders Bonus Qualifications: - Experience designing or contributing to AI/LLM-based applications backed by warehouse data (e.g., Snowflake Intelligence, Cortex, RAG, agent frameworks) - Hands-on experience with Python for data scripting, automation, or framework development - Familiarity with streaming/CDC pipelines (Streamkap, Fivetran, Kafka) and real-time analytics use cases - Experience leading a data platform migration, large-scale refactor, or modeling-standards overhaul - Experience in fintech, lending, or another regulated, data-intensive industry Compensation: Annual Targeted Salary: $160,000-$185,000 CAD Annual Target Bonus: 12% At Forward Financing, we're committed to fair and transparent compensation. We believe in providing a compensation package that recognizes your skills, experience, and the unique value you bring to our team. We take a market-based approach to pay, regularly reviewing benchmark data to ensure our compensation remains competitive, equitable, and aligned with our performance-driven culture. Final offers are determined by a variety of factors, including the candidate's qualifications, relevant experience, specific skills, and internal equity. This approach ensures that our compensation is competitive and equitable. Your recruiter will provide specific details on the expected base and variable earnings as it pertains to this specific role. This position is to fill an existing vacancy. Total Rewards:Additionally, we offer a comprehensive total rewards package, including but not limited to: medical, dental, vision, a flexible time-off policy, paid parental leave, RRSP match, wellness reimbursement, volunteering days, annual professional development budget, and charitable donation match. Forward is proud to be a remote-first company, keeping workplace flexibility a top priority for our employees. As a business, we are focused on impact; we are more concerned with your contributions to the success of the company than where you get your work done. To help facilitate in-person collaboration, employees are welcome to work from one of our premiere office locations. When we aren’t collaborating to drive business and support our customers, we’re finding virtual and in-person ways to get to know our colleagues, celebrate team wins, and have fun together!

• Design, develop, and optimize scalable dimensional data models and marts using dbt • Build and extend Forward's semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products • Help deliver the data foundation that powers AI at Forward - contributing the high-quality models, metadata, and governance that make Snowflake Intelligence and other AI/agent use cases trustworthy and production-ready • Advance Forward's data centralization vision by collaborating across BI, Data Science, Data Engineering, and Product to consolidate sources of truth and eliminate fragmented business logic • Act as the primary liaison with the Data Science team to translate features into production-ready data variables required for training and validating predictive models • Collaborate closely with the Data Engineering team to ensure the robust, reliable deployment and orchestration of data variables that feed production machine learning models • Partner with the Core Technology teams on internal application schema changes and data migrations, ensuring rigorous data accuracy validation and maintaining minimal disruption to downstream analytical models • Collaborate with the DevOps team to monitor, maintain, and contribute to our independent, high-performance streaming pipelines tailored for real-time analytics use cases • Elevate team code quality by serving as a technical reviewer for Analytics team pull requests, coaching junior members, and enforcing strict adherence to internal standards for style, maintainability, performance, and modern best practices • Evaluate, integrate, and operationalize high-value third-party data sources to strategically enrich and expand the overall data ecosystem • Champion data governance and quality across the data platform - including automated dbt tests, thorough data cataloging, lineage, and compliance with security and regulatory standards - so stakeholders *and* AI systems can both rely on the numbers.

• Design, develop, and optimize scalable dimensional data models and marts using dbt • Build and extend Forward's semantic layer and metrics standards • Help deliver the data foundation that powers AI at Forward • Advance Forward's data centralization vision • Act as the primary liaison with the Data Science team • Collaborate closely with the Data Engineering team • Partner with the Core Technology teams on internal application schema changes • Collaborate with the DevOps team • Elevate team code quality by serving as a technical reviewer • Evaluate, integrate, and operationalize high-value third-party data sources • Champion data governance and quality across the data platform

• Own the technical architecture and roadmap for our most complex Analytics Engineering initiatives - including semantic layer design, source-of-truth consolidation, and the data foundation for AI and agent-based use cases • Architect Forward's semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products • Lead the technical design of the AI-ready data platform - making the modeling, metadata, and governance decisions that make Snowflake Intelligence and other AI/agent capabilities trustworthy, performant, and production-ready • Drive technical excellence across our dbt project: model architecture, materialization and incremental strategies, performance tuning, macros, testing patterns, and CI/CD practices that scale as data volume and team size grow • Set and uphold a high bar for craftsmanship across the team - defining standards for SQL style, modeling patterns, documentation, and data quality, and modeling those standards in your own work • Mentor Senior and Analytics Engineers through hands-on code review, pairing, and design feedback - accelerating their growth into stronger technical contributors • Partner with the Manager of Analytics Engineering on technical strategy, hiring, and roadmap planning - acting as a deputy for technical decisions and unblocking the team on the hardest problems • Lead deep technical partnerships with Data Science, Data Engineering, and Core Technology - owning schema migrations, feature deployments, and streaming pipeline contributions where Analytics Engineering is on the critical path • Evaluate and operationalize high-value third-party data sources and emerging tooling (e.g., Snowflake Cortex, semantic layer frameworks, observability tools) and make recommendations that elevate the platform • Champion data governance and quality at the platform level - including dbt tests, lineage, cataloging, observability, and compliance with security and regulatory standards - so both stakeholders and AI systems can trust the numbers

• Own the technical architecture and roadmap for our most complex Analytics Engineering initiatives - including semantic layer design, source-of-truth consolidation, and the data foundation for AI and agent-based use cases • Architect Forward's semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products • Lead the technical design of the AI-ready data platform - making the modeling, metadata, and governance decisions that make Snowflake Intelligence and other AI/agent capabilities trustworthy, performant, and production-ready • Drive technical excellence across our dbt project: model architecture, materialization and incremental strategies, performance tuning, macros, testing patterns, and CI/CD practices that scale as data volume and team size grow • Set and uphold a high bar for craftsmanship across the team - defining standards for SQL style, modeling patterns, documentation, and data quality, and modeling those standards in your own work • Mentor Senior and Analytics Engineers through hands-on code review, pairing, and design feedback - accelerating their growth into stronger technical contributors • Partner with the Manager of Analytics Engineering on technical strategy, hiring, and roadmap planning - acting as a deputy for technical decisions and unblocking the team on the hardest problems • Lead deep technical partnerships with Data Science, Data Engineering, and Core Technology - owning schema migrations, feature deployments, and streaming pipeline contributions where Analytics Engineering is on the critical path • Evaluate and operationalize high-value third-party data sources and emerging tooling (e.g., Snowflake Cortex, semantic layer frameworks, observability tools) and make recommendations that elevate the platform • Champion data governance and quality at the platform level - including dbt tests, lineage, cataloging, observability, and compliance with security and regulatory standards - so both stakeholders and AI systems can trust the numbers

• Lead, coach, and develop a team of Lead and Senior Analytics Engineers - driving career growth, performance and a high-trust team culture. • Stay deeply hands-on: write and review SQL/dbt code, drive technical design, and uphold a high bar for craftsmanship, testing and documentation across our Snowflake + dbt stack. • Own the roadmap for your team’s portion of the analytics platform - prioritizing work that drives the most business impact and balancing delivery, quality and technical debt. • Drive Forward’s data centralization vision by partnering with Business Intelligence and wider Analytics group to design and deliver scalable data models, marts, and a reliable semantic layer that serves as the company’s single source of truth. • Lead the build-out of our semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products. • Translate ambiguous business problems from leadership and cross-functional stakeholders into well-scoped technical solutions, communicating tradeoffs clearly to both technical and non-technical audiences. • Champion data quality, observability, and governance - including testing, lineage, cataloging, and incident response - so stakeholders can trust the numbers. • Drive technical excellence in our dbt project: model architecture, performance tuning, incremental strategies and CI/CD practices that scale as data volume and team size grow. • Help shape our hiring bar - recruit, interview and onboard exceptional Analytics Engineers as the team continues to grow.

• Lead, coach, and develop a team of Lead and Senior Analytics Engineers - driving career growth, performance and a high-trust team culture. • Stay deeply hands-on: write and review SQL/dbt code, drive technical design, and uphold a high bar for craftsmanship, testing and documentation across our Snowflake + dbt stack. • Own the roadmap for your team’s portion of the analytics platform - prioritizing work that drives the most business impact and balancing delivery, quality and technical debt. • Drive Forward’s data centralization vision by partnering with Business Intelligence and wider Analytics group to design and deliver scalable data models, marts, and a reliable semantic layer that serves as the company’s single source of truth. • Lead the build-out of our semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products. • Translate ambiguous business problems from leadership and cross-functional stakeholders into well-scoped technical solutions, communicating tradeoffs clearly to both technical and non-technical audiences. • Champion data quality, observability, and governance - including testing, lineage, cataloging, and incident response - so stakeholders can trust the numbers. • Drive technical excellence in our dbt project: model architecture, performance tuning, incremental strategies and CI/CD practices that scale as data volume and team size grow. • Help shape our hiring bar - recruit, interview and onboard exceptional Analytics Engineers as the team continues to grow.

• Develop expertise in navigating and generating insights from internal databases (including Salesforce). • Partner with various departments to identify and outline data needs and requirements. • Work with Tableau and SQL to build customized dashboards, visual analyses, and self-serve tools for key stakeholders. • Leverage Snowflake Intelligence and Claude to build, optimize, and deploy AI-driven insights, automated reporting pipelines, or natural language querying tools for business teams. • Contribute to work across the Analytics department, including Analytics Engineering and Data Science.

• Develop expertise in navigating and generating insights from internal databases (including Salesforce). • Partner with various departments to identify and outline data needs and requirements. • Work with Tableau and SQL to build customized dashboards, visual analyses, and self-serve tools for key stakeholders. • Leverage Snowflake Intelligence and Claude to build, optimize, and deploy AI-driven insights, automated reporting pipelines, or natural language querying tools for business teams. • Contribute to work across the Analytics department, including Analytics Engineering and Data Science.