Senior Data Engineer

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 challenges. How? By leveraging LLMs where appropriate, to empower our Data Analytics and Machine Learning teams so that drug pricing is 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 a collection of open source tools like Airflow and DBT built on top of industry leading data warehouses and use Python in our daily work.

In order to be eligible for this position applicants must be based in one of the following states: Arkansas, Arizona, California, Colorado, Florida, Georgia, Kansas, Minnesota, Missouri, Nevada, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Texas, Utah, Virginia, Washington, Wisconsin.

What you will do

• Design and implement scalable, performant data models to deliver rapid insights into drivers of drug prices and cost-savings opportunities.
• Develop and optimize processes to improve the correctness and usability of 3rd party data.
• Implement data quality principles to raise the bar for reliability of data shared internally and externally.
• Implement and enforce data governance policies to ensure PII/PHI protection, security, and compliance.
• Apply AI best practices to document data engineering processes, data models.
• Be a role model and mentor to junior team members by providing technical guidance and support.

What you will bring to SmithRx

• Experience: 4+ years of industrial experience in data engineering with an advanced degree or 5+ years with an undergraduate degree in Computer Science, Information Technology, or a related field.
• Data Warehouse Technologies: Demonstrated expertise in data warehouse technologies (e.g. Snowflake).
• Programming Languages: Strong skills in Python/PySpark and SQL. Experience in other modern object-oriented languages such C#/C++, Go, Java, or Scala.
• Data Modeling: Mastery of data modeling concepts and database design principles as evidenced by production-grade implementations.
• ETL Tools & Frameworks: Hands-on experience with leading ETL tools and frameworks (e.g., Apache Spark, Apache Airflow, DBT, Looker, Superset).
• Data Lifecycle: In-depth experience with entire data lifecycle, from ingestion to processing to usability by various business functions.
• Distributed Systems: Significant contributions to development implementation, and production release of multiple data processing solutions, utilizing distributed systems.