Data & Analytics Engineer

Forus•New York, NY

1d•Onsite

About The Position

Forus is building an AI-powered network connecting doctors, pharmacies, payers, and biopharma to help patients start treatment faster and support better research and drug launches. The Data & Analytics Engineer will build the data foundation that powers the company's operations, measurement, and growth. The role designs and maintains core data models, pipelines, and reporting infrastructure so teams can access clean, trustworthy, decision-grade data. It works closely with product, operations, growth, leadership, and other stakeholders, and helps establish data and analytics engineering practices, including metric definitions, code review, pipeline management, and scalable development. The work supports product usage visibility, operational performance, and life sciences client reporting. This is a demanding role with substantial autonomy and responsibility, requiring ownership and commitment to the company's success. The role is based in person at Forus' New York office in SoHo. Forus describes its work environment as high-trust and high-autonomy, with principles emphasizing rigor, resourcefulness, direct communication, high standards, and user focus. Forus offers competitive compensation with meaningful equity for full-time employees, along with benefits including fully covered medical, vision, and dental insurance; memberships for One Medical, Talkspace, Teladoc, and Kindbody; unlimited PTO; 16 weeks of parental leave; a 401(k) plan, FSA option, commuter benefits, DashPass, and meals at the office.

Requirements

3–6 years of experience in data engineering, analytics engineering, or a technical data analyst role with production ownership.
Expert-level SQL skills.
Comfort working in a code-first environment, including versioning, testing, and documentation.
Experience designing data models that balance usability, performance, and long-term maintainability.
Familiarity with a modern data stack, such as dbt, Fivetran, Airflow, GCP, AWS, Snowflake, and Metabase or equivalents.
Strong written and verbal communication skills for effective participation in internal debates and external relationships.
A track record of moving quickly, finding shortcuts, and going to unreasonable lengths to deliver on goals.
High NPS with former teammates.

Responsibilities

Build and maintain core data models for internal analytics and client-facing insights.
Design and operate data pipelines that transform raw sources into clean, analytics-ready tables.
Create dashboards and reporting tools that support performance visibility and decision-making across product, operations, and go-to-market teams.
Define and enforce consistent metrics across teams, including core business KPIs and product usage definitions.
Help improve and scale the analytics stack.
Work with stakeholders across teams to understand data needs and translate them into reliable systems.
Contribute to internal data culture through documentation, education, and code quality standards.
Help define data and analytics engineering practices, including metric structures, code review, pipeline management, and scalable development.