Data Analytics Engineer, Bright Health Group

• The ideal candidate combines strong SQL expertise with data modeling experience and a commitment to data quality
• Strong SQL skills required for complex query design and data validation
• Experience with Python and/or Scala preferred
• Knowledge of ETL/ELT methodologies and best practices
• Understanding of data modeling concepts and techniques
• Experience with data quality management and testing frameworks
• Bachelor's degree in Computer Science, Data Science, or related field, or equivalent practical experience
• Excellent analytical and problem-solving capabilities
• Ability to manage priorities effectively in a dynamic environment
• Strong attention to detail and commitment to data quality
• Self-driven with the ability to work independently and as part of a team
• Effective communication skills to collaborate with technical and non-technical stakeholders

Desirable

• NeueHealth seeks a Data Analytics Engineer to develop and maintain our core data platforms, transforming a variety of normalized data sources into silver and gold analytics-ready data models
• In this technical role, you'll be responsible for designing and implementing data pipelines that clean, de-duplicate, and aggregate information essential to our business operations
• You will serve as the critical bridge between our data collection systems and analytics teams, ensuring that the data is properly structured for efficient analysis and reporting
• Design and implement ETL processes to convert normalized bronze-level data into our silver and gold layers
• Build and maintain robust data pipelines that clean, de-duplicate, and aggregate information
• Create standardized data models that meet the needs of analytics and reporting teams
• Establish and monitor data quality checks throughout the transformation process
• Document data lineage and transformation logic for transparency and compliance
• Partner with data engineering and analytics teams to optimize data accessibility
• Troubleshoot data quality issues and implement effective solutions
• Foster a culture of operational excellence and continuous improvement within data operations
• Approach complex data transformation challenges with creativity and a solution-oriented mindset