Data Engineer

The Engineering team at SmithRx is developing the next-generation modern pharmacy benefits management (PBM) platform to change how companies administer and manage pharmacy benefits. Our unified technology platform provides real-time actionable insights that drive cost savings, power clinical services, and result in a brilliant customer experience. A unified technology platform exists nowhere in the pharmacy benefit ecosystem to programmatically solve widespread deficiencies. The result is a PBM delivering unmatched service quality and operational efficiencies that exceeds all industry standards.

As a Data Engineer, you will be responsible for building and maintaining a single source of truth data ecosystem to meet SmithRx’s fast-growing needs. We set up data infrastructure and data pipelines, develop dimensional models, and integrate data from multiple sources in a near real-time fashion that would allow us to uncover new insights and serve our internal and external customers. You will advocate and bring best practices/methodologies, coding standards, and large-scale data warehouse design perspectives to our team.  

• Design, build, and maintain highly scalable and reliable data platforms, including data pipelines, data warehouses, and data lakes.
• Collaborate with cross-functional teams to understand their data requirements and design data solutions that meet their needs.
• Implement and optimize data governance and security policies to ensure data quality and compliance.
• Develop and maintain near real-time data processing workflows using ETL/ELT tools and scripting languages.
• Follow Kimball's methodology to design a dimensional data warehouse. Migrate tables/views from analytics databases and automate manual reports to an enterprise data warehouse.
• Identify and troubleshoot performance issues in real-time data pipelines and data warehouses.
• Keep up-to-date with emerging trends and technologies in data engineering and recommend best practices to continue improving our data platforms and enterprise data warehouse/data lake.

• BS or advanced degree in Computer Science, Information Systems, or relevant experience.
• Minimum of 3 years of experience in data engineering, data warehousing, or related field.
• Strong understanding of data modeling, dimensional data warehouse design, and SQL, SparkSQL
• Hands-on experience with at least one cloud-based data platform, (preferably AWS), as well as columnar data warehouse solutions (eg, Redshift, Snowflake, Big Query, etc)
• Proficiency in at least one scripting language, such as Python, Java, or Scala.
• Experience with data integration tools or near real-time streaming such as Apache Kafka, Apache Flink, AWS Glue, Airflow, or other stream processing frameworks.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.

• Data visualization tools like Looker
• Healthcare industry domain knowledge