Senior Staff Data Engineer

Architecture & Technical Strategy

• Define the long-term data engineering strategy guided by company-wide priorities and engineering best practices.
• Create coherent designs across multiple pipelines and API boundaries. Reduce complex concepts to foundational components and simplify infrastructure to lower maintenance costs.
• Make high-impact technical choices—including "build vs. buy" and framework selections—based on sound reasoning. Review designs to preemptively identify and resolve technical risks.
• Implement solutions that measurably improve developer efficiency and establish engineering-wide quality and best practices.

Execution & Business Impact

• Roll out major features and systems reliably, including appropriate monitoring, failure domain characterization, and success metric definitions.
• Leverage a deep understanding of SmithRx’s business strategy to identify group-wide opportunities. Proactively refocus team efforts when projects are off-course or not moving the needle for the business.
• Enforce data governance policies (PII/PHI protection, security, compliance) and implement data quality principles to raise the bar for the reliability of data shared internally and externally.

Leadership & Collaboration

• Influence the roadmaps of other SmithRx teams. Act thoughtfully and decisively in critical situations, seeking diverse perspectives but ultimately leading decision-making to move priorities forward.
• Serve as a role model and coach for other engineers, taking into account their unique skills and providing constructive feedback to maximize their impact.
• Develop focused messaging and effectively present technical strategies and business cases at the executive level.
• Break down silos, build deep cross-functional relationships, and create excitement to drive the adoption of new technologies or processes across the organization.

Requirements

• 8+ years of industrial experience in data engineering with an advanced degree or 12+ years with an undergraduate degree in Computer Science, Information Technology, or a related field (start-up and healthcare experience highly desirable).
• Demonstrated mastery of data modeling concepts, database design principles, and data warehouse technologies (e.g., Snowflake) through production-grade implementations.
• Strong skills in PySpark, SQL, and Python required. Experience in modern object-oriented or compiled languages such as C#/C++, Go, Java, or Scala is a plus.
• Hands-on experience with leading ETL tools and frameworks (e.g., Apache Spark, Apache Airflow, dbt, Looker, Superset).
• In-depth experience managing the entire data lifecycle, with direct responsibility for the development, implementation, and production release of complex data processing solutions utilizing distributed systems.
• Proven track record of making decisions optimized for the wider engineering organization rather than locally optimal outcomes, especially in environments with significant ambiguity.

Benefits

• Highly competitive wellness benefits including Medical, Pharmacy, Dental, Vision, and Life Insurance and AD&D Insurance
• Flexible Spending Benefits
• 401(k) Retirement Savings Program
• Short-term and long-term disability
• Discretionary Paid Time Off
• 12 Paid Company Holidays
• Wellness Benefits
• Commuter Benefits
• Paid Parental Leave benefits
• Employee Assistance Program (EAP)
• Professional development and training opportunities