Manager, Analytics Engineering

Forward Financing•Boston, MA

2d•$170,000 - $200,000•Remote

About The Position

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. We are seeking a Manager, Analytics Engineering to lead and grow a high-performing team of Lead and Senior Analytics Engineers and to take ownership of one of Forward's most strategic bets: building a centralized, AI-ready data foundation. This is a hands-on leadership role. You will set technical direction for a critical portion of our data platform, ship code alongside your team, and drive the build-out of our semantic layer so that a single source of truth powers our dashboards, models, and the next generation of AI experiences - including Snowflake Intelligence and other agent-based capabilities leadership is investing in. You'll partner with stakeholders across Sales, Underwriting, Account Servicing, Finance, Risk, and Product to turn complex business problems into trusted, scalable data products. Reporting to the Senior Manager of Analytics Engineering, you'll be a key partner in evolving how Forward delivers insight - and intelligence - at scale.

Requirements

7+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence with a strong foundation in SQL and dimensional/data modeling.
2+ years of people management experience leading senior individual contributors, including driving performance and career development.
Deep hands-on expertise with dbt and a cloud data warehouse (Snowflake strongly preferred), including incremental models, testing strategies, and macros.
Demonstrated experience designing and operating a semantic or metrics layer that serves as a trusted source of truth across an organization.
Track record of partnering directly with senior cross-functional leaders (Finance, Risk, Operations, Product, etc.) to translate business problems into durable data products.
Excellent written and verbal communication skills - able to make complex technical decisions accessible to executives and non-technical partners.
Proven ability to coach engineers, raise the technical bar, and deliver consistently against an ambitious roadmap.

Nice To Haves

Experience integrating AI or LLM-based capabilities into the analytics stack (e.g., Snowflake Intelligence).
Experience in fintech, lending, or another regulated, data-intensive industry.
Experience with streaming data or CDC pipelines (Streamkap, Fivetran, or similar) and real-time analytics use cases.
Familiarity with BI tools such as Tableau, Looker, or similar.
Python proficiency for data transformations or workflow tooling.

Responsibilities

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.