Job Responsibilities
- Work with cross-functional agile team members throughout the software development lifecycle to conceptualize, ideate, prototype, build, monitor and maintain a high-quality foundational data layer for the platform architecture
- Build new application data models and optimize existing data models using relational (SQL) and document-oriented (NoSQL) database technology
- Design and build data lakes and analytic data services to support reporting, analytics and AI services
- Advise and influence the selection of purpose-built database technology and architecture that fits each problem domain, whether SQL or NoSQL
- Architect cloud-based data pipelines, data services, and data access patterns to achieve and balance needs for high performance, reliability, and cost efficiency
- Contribute to solutions for quality assurance, performance testing and load testing of data-centric services
- Contribute to solutions for creating application test data for scale testing
- Troubleshoot and resolve complex issues involving data, queries and performance
- Mentor team members on data architecture topics including query performance optimization
- Other duties as assigned
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, or related field (or equivalent experience)
- Minimum of 10 years of professional experience as a data architect and data engineer
- Experience building modern, cloud-native applications using cloud hosted databases
- Experience building data centric applications and tools in Python
- Interest in building enterprise software with deep customer empathy, taking pride in contributing to a world class end-to-end user experience
- Strong problem-solving, collaboration, teamwork and communication skills
- Eagerness to learn and adapt to new technologies and tools
- Deep understanding of:
- SQL and NoSQL databases, query optimization, and database indexing
- Techniques and tooling for monitoring and improving database performance
- ETL data pipelines
- Change management methodologies for incremental enhancement and change of data schemas, including versioning and rollback
- Version control systems (Git)
- CI/CD tools such as GitHub Actions or similar
- Cloud platforms (AWS, Azure, or Google Cloud)
- Modern software development lifecycle on an agile product team
Preferred Qualifications
- Comfortable working with Infrastructure as Code in AWS
- Exposure to data science tooling in Python (numpy, scipy, scikit-learn, pandas)

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