Data & Analytics Engineer

Forus•New York, NY

1d•Onsite

About The Position

As a Data & Analytics Engineer at Forus, you’ll build the data foundation that powers how we operate, measure, and grow. You’ll design and maintain our core data models, pipelines, and reporting infrastructure — ensuring the right people have access to clean, trustworthy, decision-grade data at the speed we need to move. This is a cross-functional, impact-heavy role where you’ll work closely with product, ops, growth, and leadership to build the systems that enable better, faster decisions across the company. You’ll also help define our data & analytics engineering practices: how we structure metrics, review code, manage pipelines, and build for scale. Your work will directly support everything from product usage visibility to operational performance to life sciences client reporting. This is a demanding role, with a high level of autonomy and responsibility. You will be expected to "act like an owner" and commit yourself to Forus' success. If you are low-ego, hungry to learn, and excited about intense, impactful work that drives both company growth and accelerated career progression, we want to hear from you.

Requirements

3–6 years of experience in data engineering, analytics engineering, or a technical data analyst role with production ownership
Expert-level SQL and comfort working in a code-first environment (versioning, testing, documentation)
Experience designing data models that balance usability, performance, and long-term maintainability
Familiarity with the modern data stack — dbt, Fivetran, Airflow, GCP/AWS/Snowflake, Metabase (or equivalents)
Strong written and verbal communication that allows you to be an effective participant in both internal debates and external relationships
Track record of moving quickly, finding shortcuts, and going to unreasonable lengths to deliver on goals
High NPS with your former teammates

Responsibilities

Build and maintain the core data models that serve as the foundation for internal analytics and client-facing insights
Design and operate the data pipelines that transform raw sources into clean, analytics-ready tables
Create dashboards and reporting tools that drive performance visibility and decision-making across product, ops, and GTM
Define and enforce metric consistency across teams — including core business KPIs and product usage definitions
Help improve and scale our analytics stack (we use GCP BigQuery and Dataform, Fivetran, Postgres, and dashboarding tools)
Collaborate 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