Senior Analytics Engineer

Meridian Softworks 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 Senior Analytics Engineer, you will design, build, and maintain the data models and semantic layer that power Forward - collaborating with Data Engineering, Data Science, DevOps, Business Intelligence, and Product. You'll help shape and operate our modern analytics platform (dbt, Fivetran, Snowflake, Datafold, Tableau) and play a direct role in building the AI-ready data foundation that supports Snowflake Intelligence, agent-based use cases, and machine learning at Forward - delivering high-quality data products that drive innovation and informed decision-making across the organization. In This Role You Will: 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 Role Requirements: (Even if you don't check every box, but see yourself contributing, please apply.) 4+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence 2+ years of hands-on experience developing and maintaining production-level data transformation pipelines using dbt or equivalent scripting experience in Python 2+ years of experience with a cloud-based data warehouse such as Snowflake or Redshift Advanced proficiency in SQL and dimensional data modeling, with a track record of building models that are durable, well-tested, and easy for downstream consumers to use Demonstrated strong ability to quickly translate complex business needs and ambiguous requirements into robust, scalable technical data solutions Bonus Qualifications: Hands-on experience with Python for data scripting, automation, or predictive modeling support Experience designing or contributing to a semantic layer / metrics layer that serves as an organizational source of truth Experience building data products that support AI, LLM, or agent-based applications (e.g., Snowflake Intelligence, Cortex, RAG over warehouse data, or similar) Familiarity with streaming/CDC pipelines (Streamkap, Fivetran, Kafka) and real-time analytics use cases Experience in fintech, lending, or another regulated, data-intensive industry Compensation: Annual Ta