Data Engineer

Position Overview

• Location Type: Not specified
• Employment Type: Not specified
• Salary: Not specified

RxSense is a leading healthcare technology company delivering innovative solutions for pharmacy benefits and prescription savings. Our enterprise platform brings transparency, flexibility, and efficiency to pharmacy benefit management, helping clients streamline operations and enabling consumers to save on prescriptions. By integrating intelligence across the pharmacy ecosystem, RxSense makes cost-effective healthcare more accessible. Whether for PBMs, pharmacies, or individuals, our solutions help modernize operations, reduce costs, and improve outcomes.

RxSense also owns and operates SingleCare, a free prescription savings service that offers consumers access to consistently low prices on prescription drugs. Through its partnerships with the country’s largest pharmacies and grocers, including CVS, Walgreens, Walmart, Kroger and Albertsons, SingleCare improves access and adherence to affordable medications and has helped millions of Americans save over $11 billion on their medications.

RxSense is a great place to work! Our company has earned several prestigious awards, including Fast Company’s Most Innovative Companies, Forbes’ Top Startup Employers, Modern Healthcare’s Best Places to Work in Healthcare, and Inc’s Best in Business and Best Workplaces.

Requirements

• Experience: At least 5 years of hands-on experience in data engineering.
• Technical Skills:
  • Strong foundation in data engineering best practices.
  • Experience with Snowflake.
  • Experience with SQL Server.
  • Experience with AWS.
  • Experience with Matillion ETL.

Responsibilities

• Data Pipeline Development and Maintenance:
  • Design, develop, and maintain scalable and high-performance ETL pipelines using Matillion ETL to ingest, transform, and load data into Snowflake.
  • Integrate and manage data from various sources, ensuring data quality, reliability, and performance.
  • Optimize SQL queries, scripts, and stored procedures in Snowflake and SQL Server to improve efficiency and reduce processing time.
• Data Warehousing and Modeling:
  • Develop and implement data models within Snowflake to support business intelligence and analytics requirements.
  • Collaborate with data architects and analysts to design and enhance data warehouse schemas and ensure alignment with reporting and analytics.
• Collaboration and Requirements Gathering:
  • Work with business stakeholders to understand data requirements and translate them into technical specifications.
  • Support data architects and analysts by providing guidance on data ingestion, storage, and retrieval methods.
• Platform Monitoring and Optimization:
  • Monitor data pipeline and ETL performance, identifying bottlenecks and making necessary adjustments to ensure efficiency.