Description

You will design and implement cloud-based data analytic solutions to derive business-ready insights from big data.

Responsibilities

• Design and implement scalable, resilient end-to-end data analytic pipelines.
• Translate complex analytical concepts into modularized software components.
• Lead data analysts and engineers to mature proof-of-concepts into production-grade solutions.
• Automate manual reporting and analytic processes using cloud-native technologies.
• Investigate healthcare data to identify abnormalities and suggest mitigation steps.

Required Skills

• 7+ years of experience designing and implementing production-grade data analytic solutions in Scala and Python.
• Extensive experience with PySpark for big data processing.
• 5+ years of experience working with large-scale data and developing SQL queries.
• 3+ years of hands-on experience with AWS EMR, Airflow, and RedShift.
• 3+ years of experience with Business Intelligence tools such as Tableau, Cognos, Qlik, or Pyramid.
• 3+ years of experience leveraging statistical techniques to surface patterns and data abnormalities.
• Proficiency with Git, linting, and unit/integration testing.
• Experience leading data analysts and engineers in modularized pipeline design and test-driven development.
• Bachelor’s Degree in Computer Science, Engineering, or a quantitative field.

Preferred Skills

• Experience with healthcare industry data such as X12, CPT/HCPCS, or ICD-10.
• Experience in data architecture, cloud engineering, and observability in production.
• Familiarity with Agile/Scrum environments and JIRA.

Key Skills

Education

Bachelor’s Degree