Senior Staff Data Engineer at SmithRx

Job description

Who We Are: SmithRx is a rapidly growing, venture-backed Health-Tech company. Our mission is to disrupt the expensive and inefficient Pharmacy Benefit Management (PBM) sector by building a next-generation drug acquisition platform driven by cutting edge technology, innovative cost saving tools, and best-in-class customer service. With hundreds of thousands of members onboarded since 2016, SmithRx has a solution that is resonating with clients all across the country. We pride ourselves for our mission-driven and collaborative culture that inspires our employees to do their best work. We believe that the U.S healthcare system is in need of transformation, and we come to work each day dedicated to making that change a reality. At our core, we are guided by our company values: Integrity: Our purpose guides our actions and gives us confidence in the path ahead. With unwavering honesty and dependability, we embrace the pressure of challenging the old and exemplify ethical leadership to create the new. Courage: We face continuous challenges with grit and resilience. We embrace the discomfort of the unknown by balancing autonomy with empathy, and ownership with vulnerability. We boldly challenge the status quo to keep moving forward—always. Together: The success of SmithRx reflects the strength of our partnerships and the commitment of our team. Our shared values bind us together and make us one. When one falls, we all fall; when one rises, we all rise. Job Summary: On the Data Engineering team, we transform streams of data into insights that solve real-world Pharmacy Benefits Management (PBM) challenges. We empower our Data Analytics and Machine Learning teams to make drug pricing transparent and easy to understand. We deliver business impact by designing, implementing, and maintaining distributed systems to collect, aggregate, and govern pharmaceutical data. We leverage open-source tools like Airflow and DBT built on top of industry-leading data warehouses (e.g., Snowflake), utilize LLMs to optimize workflows, and use Python heavily in our daily work. What you will do: Architecture & Technical Strategy Define Technical Vision: Define the long-term data engineering strategy guided by company-wide priorities and engineering best practices. Design Ecosystems: Create coherent designs across multiple pipelines and API boundaries. Reduce complex concepts to foundational components and simplify infrastructure to lower maintenance costs. Drive Engineering Excellence: 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. Improve Developer Efficiency: Implement solutions that measurably improve developer efficiency and establish engineering-wide quality and best practices. Execution & Business Impact Deliver at Scale: Roll out major features and systems reliably, including appropriate monitoring, failure domain characterization, and success metric definitions. Align with Business Goals: 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. Manage Data Quality & Governance: 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 Cross-Functionally: 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. Mentor and Develop: Serve as a role model and coach for other engineers, taking into account their unique skills and providing constructive feedback to maximize their impact. Executive Communication: Develop focused messaging and effectively present technical strategies and business cases at the executive level. Champion Organizational Change: Break down silos, build deep cross-functional relationships, and create excitement to drive the adoption of new technologies or processes across the organization. What you will bring to SmithRx: 8+ years of 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 is 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 are 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. A proven track record of making decisions optimized for the wider engineering organization rather than locally optimal outcomes, especially in environments with significant ambiguity. What SmithRx Offers You: 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) Well-stocked kitchen in office locations Professional development and training opportunities Zone A includes the following locations: San Francisco Bay Area - California Metro New York City - Connecticut, New Jersey, New York and Pennsylvania Zone A Pay Range $214,200 — $252,000 USD Zone B includes the following locations: California - outside of San Francisco Bay Area Metro Denver / Boulder - Colorado Metro District of Columbia - District of Columbia, Maryland, Virginia and West Virginia Metro Boston / Cambridge - Massachusetts and New Hampshire Metro Austin - Texas Metro Seattle - Washington Zone B Pay Range $196,400 — $231,000 USD Zone C includes all other locations not listed above, including: Alabama, Alaska, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Rhode Island, South Carolina, South Dakota, Tennessee, Utah, Vermont, Wisconsin, Wyoming Non metro Colorado, Connecticut, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Texas, Virginia, Washington, and West Virginia Zone C Pay Range $178,500 — $210,000 USD Compensation & Benefits Base Salary: The range listed above reflects our standard pay scale and actual pay will vary based on work location, job level, job-related knowledge, skills, and experience. Total Rewards: In addition to base pay, this role may be eligible for bonuses, commissions, or equity. SmithRx offers a variety of benefits to help you live well, including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance and 401(k). Individual offers are tailored to your geography, experience, skills, and education. Your recruiter can share more specific details during the hiring process. In the meantime, feel free to explore our comprehensive benefits here .

Requirements

Must-haves

Architecture & Technical Strategy
Define Technical Vision: Define the long-term data engineering strategy guided by company-wide priorities and engineering best practices.
Design Ecosystems: Create coherent designs across multiple pipelines and API boundaries. Reduce complex concepts to foundational components and simplify infrastructure to lower maintenance costs.
Drive Engineering Excellence: 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.
Improve Developer Efficiency: Implement solutions that measurably improve developer efficiency and establish engineering-wide quality and best practices.
Execution & Business Impact
Deliver at Scale: Roll out major features and systems reliably, including appropriate monitoring, failure domain characterization, and success metric definitions.
Leadership & Collaboration
Mentor and Develop: Serve as a role model and coach for other engineers, taking into account their unique skills and providing constructive feedback to maximize their impact.
Executive Communication: Develop focused messaging and effectively present technical strategies and business cases at the executive level.
Champion Organizational Change: Break down silos, build deep cross-functional relationships, and create excitement to drive the adoption of new technologies or processes across the organization.
Demonstrated mastery of data modeling concepts, database design principles, and data warehouse technologies (e.g., Snowflake) through production-grade implementations.
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.
A proven track record of making decisions optimized for the wider engineering organization rather than locally optimal outcomes, especially in environments with significant ambiguity.
Flexible Spending Benefits
Short-term and long-term disability
Wellness Benefits
Well-stocked kitchen in office locations
Professional development and training opportunities
San Francisco Bay Area - California
Metro New York City - Connecticut, New Jersey, New York and Pennsylvania
California - outside of San Francisco Bay Area

Nice-to-haves

Strong skills in PySpark, SQL, and Python are required. Experience in modern object-oriented or compiled languages such as C#/C++, Go, Java, or Scala is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpythonapisqlgojava

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness

Professional Development