Lead Analytics Engineer

Aperture Cloud 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