Job Description
Position Overview
As a Staff Data Architecture Engineer, you will work with a fast-moving, ambitious team, building our data-centric, AI-driven Contract Lifecycle Management software solutions. You will collaborate with product domain experts, application software engineers, and Cloud Ops engineers, to architect, build, maintain and optimize data models, databases, and data centric services.
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 architectureBuild new application data models and optimize existing data models using relational (SQL) and document-oriented (NoSQL) database technologyDesign and build data lakes and analytic data services to support reporting, analytics and AI servicesAdvise and influence the selection of purpose-built database technology and architecture that fits each problem domain, whether SQL or NoSQLArchitect cloud-based data pipelines, data services, and data access patterns to achieve and balance needs for high performance, reliability, and cost efficiencyContribute to solutions for quality assurance, performance testing and load testing of data-centric servicesContribute to solutions for creating application test data for scale testingTroubleshoot and resolve complex issues involving data, queries and performanceMentor team members on data architecture topics including query performance optimizationOther duties as assignedRequired 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 engineerExperience building modern, cloud-native applications using cloud hosted databasesExperience building data centric applications and tools in PythonInterest in building enterprise software with deep customer empathy, taking pride in contributing to a world class end-to-end user experienceStrong problem-solving, collaboration, teamwork and communication skills Eagerness to learn and adapt to new technologies and toolsDeep understanding of:SQL and NoSQL databases, query optimization, and database indexingTechniques and tooling for monitoring and improving database performanceETL data pipelinesChange management methodologies for incremental enhancement and change of data schemas, including versioning and rollbackVersion control systems (Git)CI/CD tools such as GitHub Actions or similarCloud platforms (AWS, Azure, or Google Cloud)Modern software development lifecycle on an agile product teamPreferred Qualifications
Comfortable working with Infrastructure as Code in AWSExposure to data science tooling in Python (numpy, scipy, scikit-learn, pandas)
