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Senior Analytics Engineer

Princeton, NJ, Boston, MA, NYC, NY

We are a healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. Our technology helps enterprise and partnership clients simplify their businesses and helps consumers save on prescriptions.

As a leader in SaaS technology for healthcare, we offer innovative solutions with integrated intelligence on a single enterprise platform that connects the pharmacy ecosystem.  With our expertise and modern, modular platform, our partners use real-time data to transform their business performance and optimize their innovative models in the marketplace.

Position Summary:
The Data Science team collaborates closely with the company's Finance, Pricing, and Analytics teams to develop algorithms that create a competitive advantage. The Senior Analytics Engineer is a key member of the Data Science team, building data models and pipelines to support marketing and dynamic pricing strategies for our direct-to-consumer business. Leveraging expertise in data modeling, using Python, SQL, and ETL frameworks (such as airflow, dbt etc.), the Senior Analytics Engineer will apply best practices of software engineering and business intelligence in the production, management, and maintenance of data essential for the company's reporting, data analyzing, and advanced machine learning workflows.

Job Responsibilities:

  • Collaborate with business stakeholders, data scientists, and machine learning engineers to identify, understand, and anticipate data needs, including developing formats for capturing KPIs and designing data structures to support strategic decisions and analytical initiatives.
  • Design and implement fact and dimension tables optimized for business analysts, enabling efficient reporting and detailed analysis of key business metrics.
  • Develop and maintain automated production processes for integrating multiple data sources, including validation and verification to ensure data integrity.
  • Partner with Engineering teams to source data reliably and scalability through automation.
  • Design, build, and maintain efficient data transformation pipelines and final tables, supporting data governance best practices and data integrity standards.
  • Research industry best practices in data pipeline design and implement improvements accordingly.
  • Assist Data Scientists by preparing data sets optimized for feature engineering and modeling efforts.

Qualifications: 

  • Bachelors degree with 4 plus years of related professional experience; or an equivalent combination of education and experience.
  • Expert-level SQL skills. Expert-level to tune query performance and cost. 
  • Expert-level experience with DBT or comparable data transformation frameworks. 
  • Expert-level proficiency with Python and Airflow. 
  • Extensive knowledge of cloud-based big data platforms (BigQuery, Snowflake, Redshift).
  • Experience developing or directly supporting machine learning models.
  • Familiarity with AI prompt engineering methods and leveraging AI technologies in analytical workflows. 
  • Familiarity with modern data stack tools, including CI/CD practices, version control (Git), data observability tools (e.g., Monte Carlo, Datafold), and data cataloging/governance platforms

Salary Range: $98,000 - $140,000

RxSense believes that a diverse workforce is a more talented and productive workforce. As such, we are an Equal Opportunity and Affirmative Action employer. Our recruitment process is free from discriminatory hiring practices and all qualified applicants are considered for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity, ancestry, age, or national origin.  Neither will qualified applicants be discriminated against on the basis of disability or protected veteran status.  We believe in the strength of the collaboration, creativity and sense of community a diverse workforce brings. 

In Office Policy:  Candidates within a commutable distance to one of the offices listed below will be expected to commit to a hybrid in office schedule if selected.

  • Boston, MA
  • Princeton, NJ
  • New York City, NY
  • West Palm Beach, Florida

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