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Software Engineer Principal

Home Depot is hiring a Software Engineer Principal in STORE SUPPORT CENTER, ATLANTA - 9090, United States of America (Full time).

  • Home Depot
  • STORE SUPPORT CENTER, ATLANTA - 9090, United States of America
  • Full time

With a career at The Home Depot, you can be yourself and also be part of something bigger. Key Responsibilities: • Collaborate and pair with other product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutions. • Document, review and ensure that all quality and change control standards are met. • Write custom code or scripts to automate infrastructure, monitoring services, and test cases. • Write custom code or scripts to do "destructive testing" to ensure adequate resiliency in production. • Create meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively. • Contribute to enterprise-wide tools to drive destructive testing, automation, or engineering empowerment. • Identify product enhancements (client-facing or technical) to create a better experience for the end users. • Identify unsecured code areas and implement fixes as they are discovered with or without tooling. • Identify, implement, and share technical solutions that can be used across the organization. • Create and architect foundational code elements that can be reused many times by a product. • Create meaningful architecture diagrams and other documentation needed for security reviews or other interested parties. • Define Service Level Objectives for product to constantly measure their reliability in production and help prioritize backlog work. • Field questions from other product teams or support teams. • Monitor tools and participate in conversations to encourage collaboration across product teams. • Provide application support for software running in production. • Proactively monitors production Service Level Objectives for products. • Work with vendors and the open-source community to help identify and implement feature enhancements in software products. • Work with other product teams to create API specifications and contracts for shared data. • Proactively review the performance and capacity of all aspects of production: code, infrastructure, data, and message processing. • Triage high priority issues and outages as they arise. • Participate in and lead learning activities around modern software design and development core practices (communities of practice). • Learn, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizations. • Attend conferences and learn how to apply new technologies where appropriate. • Telecommuting available. Minimum Qualifications: • Must be eighteen years of age or older. • Must be legally permitted to work in the United States. • Bachelor’s degree in Computer Science, Computer Information Systems, Information Technology, or a related field and 7 years of experience in a related occupation. Requires 5 years of experience in the following skills: • Designing and implementing Enterprise Data Warehouse architectures including Star Schema; • Cloud-native warehouses, especially BigQuery; • Designing highly-optimized reusable Analytical Data Sets; • Implementing Data Governance and Security and Role-Based Access Controls; • SQL; • Writing SQL queries against cloud-native databases like BigQuery, on-prem databases like db2; • Python; • OLAP databases and aggregation strategies; • Data-related aspects of Google Cloud Platform; • Orchestration and DataOps to build and maintain complex data pipeline workflows; • Optimizing cloud storage and compute costs through efficient partitioning, clustering and storage tiering strategies; • Retail Omnichannel Integration experience managing disparate data across the retail ecosystem; • Retail logic including sales, inventory and supply chain logic; • Defining and guiding a team of data engineers to execute a 1-3 year data strategy balancing business needs with long-term data architecture needs; • Translating complex business data problems into technical solutions; • CI/CD toolchain; • Version control systems (Git); • NoSQL databases; • Query optimization and troubleshooting, specifically on BigQuery with slot management.