Data Engineer Intern

GoodRx is America's healthcare marketplace. Each month, millions of people visit goodrx.com to find reliable health information and discounts for their healthcare - and we've helped people save $60 billion since 2011. We provide prescription discounts that are accepted at more than 70,000 pharmacies in the U.S., as well as telehealth services including doctor visits and lab tests. Our services have been positively reviewed by Good Morning America, The New York Times, NBC News, AARP, and many others.

Our goal is to help Americans find convenient and affordable healthcare. We offer solutions for consumers, employers, health plans, and anyone else who shares our desire to provide affordable prescriptions to all Americans.

Responsibilities:

• Collaborate with product managers, data scientists, data analysts and engineers to define requirements and data specifications.
• Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Airflow, Redshift, EMR.
• Develop, deploy and maintain serverless data pipelines using Event Bridge, Kinesis, AWS Lambda, S3 and Glue.
• Define and manage overall schedule and availability for a variety of data sets.
• Work closely with other engineers to enhance infrastructure, improve reliability and efficiency.
• Make smart engineering and product decisions based on data analysis and collaboration.
• Act as in-house data expert and make recommendations regarding standards for code quality and timeliness.
• Architect cloud-based data infrastructure solutions to meet stakeholder needs.

• Bachelor's degree in analytics, statistics, engineering, math, economics, science or related discipline.
• Experience in any one of the Cloud data spaces such as AWS, Azure or GCP.
• Experience in engineering data pipelines using big data technologies (Python, pySpark, Real-time data platform like Active MQ or Kafka or Kinesis) on large scale data sets.
• Experience writing complex SQL and ETL development with experience processing extremely large data sets.
• Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions.
• Familiarity with AWS Services (S3, Event Bridge, Glue, EMR, Redshift, Lambda).
• Ability to quickly learn complex domains and new technologies.
• Innately curious and organized with the drive to analyze data to identify deliverables, anomalies and gaps and propose solutions to address these findings.
• Experience using Jira, GitHub, Docker, CodeFresh, Terraform.
• Experience contributing to full lifecycle deployments with a focus on testing and quality.
• Experience with data quality processes, data quality checks, validations, data quality metrics definition and measurement.