Data Engineer, Product - FuturHealth

At FuturHealth, we're on a mission to create a product where every individual feels inspired and empowered to confidently take charge of their wellbeing. We believe in and are dedicated to offering personalized and holistic approaches to combat health concerns.

Operating at the intersection of health and technology, we provide a comprehensive range of services, including telemedicine, personalized nutrition plans, medication delivery, and insurance solutions.

About the Role

This is a hybrid, high-ownership role for an engineer who cares deeply about both the code and the context. You are equally comfortable building an ingestion pipeline, modeling data in dbt, and sitting down with stakeholders to figure out the why behind a metric.

You will own data end-to-end: ingesting and orchestrating raw data, modeling it in dbt, exposing it through self-service BI, and ensuring our business stakeholders are empowered with trustworthy data.

What You Will Do

• Design, build, and maintain reliable ETL/ELT pipelines.
• Own the dbt models and datasets that serve as the source of truth for key business metrics.
• Govern the semantic layer so metric definitions stay consistent and documented across reporting surfaces.
• Implement testing and observability for analytics pipelines, and bring in tooling that strengthens the stack.
• Partner with analysts and stakeholders to gather requirements and turn them into clean, well-scoped solutions.
• Run hands-on analysis and deep dives: KPIs, release performance, and A/B tests.
• Take end-to-end ownership: jump into unfamiliar codebases, data sources, and business domains and figure out how to ship reliable, scalable solutions.
• Leverage AI tools and agentic workflows (OpenCode, Claude Code, Zed, and Eve) to write code and debug faster, while helping build natural-language querying tools/agents for non-technical stakeholders.

It’s a Perfect Match If You Have

• 3–5+ years as an analytics engineer, data engineer, or similar role.
• Strong knowledge of SQL, Python, dbt, and modern data modeling best practices.
• Comfortable with large-scale data systems (BigQuery, Snowflake, etc.).
• Strong familiarity with CI/CD, Git-based workflows, and automated testing.
• Proficiency in data analysis and BI tools (Looker, Tableau, Power BI).
• Adaptable and fast-learning, with a strong bias for ownership and a habit of leveraging AI to work faster.
• Statistics and experiment analysis (A/B testing, segmentation, metric definition).
• Experience leveraging AI to accelerate coding lifecycle and enabling AI-driven analytics for stakeholders.
• Clear communication and real stakeholder instincts.

Preferred Qualifications

• Experience with our stack: GCP, and building/maintaining Cloud Composer / Airflow DAGs.
• LookML and semantic-layer / metric-governance experience.
• Subscriptions experience (retention, rebill/refill, LTV).
• Cloud-native pipelines (Cloud Functions, GCP Logging/Monitoring) and data-job alerting.
• Healthcare, telehealth, or MSO experience.
• Fast-paced or startup environments.