- Design, build, and maintain features across the stack using TypeScript, Node.js, PostgreSQL, and MongoDB
- Architect and implement scalable APIs, real-time data processing, and AI-driven features
- Own end-to-end feature development from technical design through implementation, testing, and deployment
- Build in-product experiences that expose insights and analytics to university stakeholders
- Design and build ETL pipelines and data transformation workflows
- Create and maintain Looker dashboards in collaboration with business stakeholders
- Build data models and aggregation layers for efficient querying and real-time analytics
- Implement data validation, change management, quality checks, and monitoring
- Serve as the data engineering SME for the engineering team, providing guidance on data architecture decisions
- Optimize database schemas, queries, and indexing strategies for performance at scale
- Partner with product, engineering, and business teams to understand analytics requirements and deliver data-driven features
- Mentor team members on data modeling, pipeline development, and analytics best practices
- Assist other teams in improving their data structures along with migration and backfill strategies
Node.jsPostgreSQLArtificial Intelligence+6 more