SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
SmithRx is a venture-backed healthtech company disrupting the Pharmacy Benefit Management (PBM) sector with a next-generation drug acquisition platform. The company has onboarded hundreds of thousands of members since 2016 and is focused on making the U.S. healthcare system more transparent and efficient through technology and innovation.
As a Senior Staff Data Engineer, you will lead the technical vision and strategy for the data engineering function, transforming pharmaceutical data streams into actionable insights that solve real-world PBM challenges. You'll design and maintain distributed systems that collect, aggregate, and govern data using modern tools like Apache Airflow, dbt, Snowflake, and Python, while leveraging LLMs to optimize workflows.
Key responsibilities include:
**Architecture & Strategy:** Define long-term data engineering strategy aligned with company priorities. Design coherent systems across multiple pipelines and API boundaries. Make high-impact technical decisions (build vs. buy, framework selection) based on sound engineering principles. Implement solutions that measurably improve developer efficiency and establish company-wide quality standards.
**Execution & Impact:** Deliver major features and systems reliably with appropriate monitoring and success metrics. Align technical work with business strategy and proactively refocus efforts when projects drift. Enforce data governance policies (PII/PHI protection, security, compliance) and implement data quality principles.
**Leadership & Collaboration:** Influence cross-functional roadmaps and lead decision-making in critical situations. Mentor and coach other engineers, providing constructive feedback. Communicate technical strategies and business cases effectively to executives. Champion organizational change by breaking down silos and driving adoption of new technologies.
You'll work with a mission-driven, collaborative team guided by values of integrity, courage, and partnership. The role requires deep expertise in data modeling, database design, and data warehouse technologies, with production-grade implementation experience.
