Lead Data Engineer

Innovate in Charlotte

Thank you for dedicating your time and talent to Lowe's. We want to give you more opportunities to learn and grow, so if you find a position you're interested in below, we encourage you to apply!

The main purpose of this role is to deliver end-to-end data solutions for complex business problems. This role includes translating business needs to technical requirements, designing the architecture, and facilitating the implementation and maintenance of those solutions. This role serves as a technical expert to develop the right solution, including the evaluation of the best fit platform/technology stack, ensuring correct implementation, following best practices and accounting for both functional and non-functional requirements such as reliability, scalability, performance, stability, security, and long-term maintainability.

• Resolve complex problems spanning multiple applications to deliver value; lead products with significant business implications, participate in planning, estimation, and prioritization in tandem with the respective product manager, and advise other engineers; execute with limited guidance.
• Evaluate and facilitate decisions on build versus buy as well as best fit platform suitable for the business problem.
• Lead development of integrated business and/or enterprise application solutions to ensure specifications are flexible, scalable, and maintainable and meet architectural standards.
• Mentor and advise others in all software development lifecycle phases by applying and sharing an in-depth understanding of company and industry methodologies (Agile and Kanban), policies, standards, controls, current architectural standards, and guidelines.
• Establish best source control and continuous integration/continuous deployment (CI/CD) practices for efficient testing and deployment of code to different environments.
• Communicate changes in software architecture and coach others to apply this understanding to data or platform solutions; lead the resolution of production incidents along with root cause analysis.
• Work across multiple domains to define and design a data lake/data solution to meet business needs and product objectives and key results, service level agreements, data quality, data governance, and observability.
• Partner with platform, architecture, and various stakeholders to design and architect solutions meeting business needs.
• Continuously improve efficiency of data pipelines and extract, transform, load (ETL) processes across the organization.
• Analyze and organize data to evaluate the usefulness and relevance of data required for insights requested by business.
• Design, lead, and deliver the development, maintenance, and enhancements of operational, analytical (including self-serve) applications across various business domains, providing direction to matrixed engineering resources to deliver reports on-premises and cloud infrastructure, creating frameworks and reusable components.
• Lead infrastructure-related projects from idea generation through implementation, including needs analysis, cost/benefit analysis, selection, implementation, knowledge transfer, and support.
• Analyze and propose design alternatives, facilitate appropriate design decisions, and assess risk, cost, schedule, and resource tradeoffs; understand networking, including subnetting, routing, virtual private cloud/virtual network, security groups, and load balancing.

• Bachelor's degree in engineering, computer science, computer information systems (CIS), or related field or equivalent years of experience in lieu of education requirement, if applicable
• 7 years of experience in data, business intelligence, or platform engineering, data warehousing/ETL, or software engineering
• 6 years of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC)
• 4 years of expertise in object-oriented programming/structure programming, SQL, and scripting
• 4 years of experience in big data and Cloud big data technologies

• Master's degree in computer science, CIS, or related field
• 6 years of IT experience developing and implementing business systems within an organization
• 4 years of experience leading teams, with or without direct reports
• 4 years of experience working with CI/CD tools
• 7+ years of data engineering experience, with a focus on building and scaling data pipelines within GCP (Google Cloud Platform) using Spark
• Expert-level proficiency in Python and SQL for complex data manipulation and transformation
• Proven experience implementing CI/CD pipelines and automated testing for data workloads
• Deep expertise in Data Modelling (Star Schema, Snowflake, or Data Vault) to support large-scale analytics
• Hands-on experience developing and deploying enterprise-grade dashboards in Looker and PowerBI
• Practical experience or a demonstrated project portfolio involving GenAI or LLM integration within data pipelines

Lowe's…