Lead Online Data Engineer

Job description

With a career at The Home Depot, you can be yourself and also be part of something bigger. Position Purpose: Consistent with The Home Depot’s commitment to openness and transparency, we are informing you that a qualified in-line successor is being considered for this position. However, all interested candidates are strongly encouraged to apply. No selection decision has been made, and the final decision will be based solely upon choosing the most qualified and suitable candidate for the position. Online Data Engineer teams at The Home Depot translate business requirements and build the infrastructure needed to capture customer, financial, or operational data. They acquire datasets that align with business needs and develop algorithms to transform data into useful, actionable information. Additionally, they build, test, and maintain database pipeline architectures. They create new data validation methods and data analysis tools. Data Engineers develop application programming interfaces (APIs) to retrieve data. Our Data Engineers develop, host, and maintain in-house enterprise solutions to improve reliability and confidence through monitoring, continually testing, and validating the products we support. These associates use big-data techniques to cleanse, organize and transform data and to maintain, defend and update data structures and integrity on an automated basis. The Lead Online Data Engineer position operates as a functional / technical expert in the discipline, and is responsible for the establishment of best practices for sustainable data solutions. In addition, they act as a formal mentor to guide the engineers / senior engineers in development of their solutions and providing overall technical guidance and oversight to ensure the solution meets the needs of the organization and does not pose risk or undue harm. Key Responsibilities: 20% - Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Partner with Other Orgs to understand potential for new tools and ways to maintain technical agility for advanced analytics. 25% - Project Management & Team Support - Lead and manage large and complex projects and teams; Provide direction on prioritization of work and ensure quality of work; Collaborate with managers and team in the distribution of workload and resources; Serve as a technical subject matter expert (SME) on both predictive and prescriptive analytics; Drive effective Agile project delivery protocols to assure we gather and surface reliable, actionable enterprise level analytics; Ensure the team comprehends and applies the established processes and standards and mentor team on development. 30% - Solution Development - Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation; Develops solutions to transform data into useful, actionable information. 25% - Technical Exploration & Development - Guide and direct project teams in the requirements gathering, design, and development of complex applications/programs; Provide technical education on advanced analytics to analytics community; Drive analytics teams to get matured in predictive and prescriptive analytics. Direct Manager/Direct Reports: This position reports to the Senior Manager or Above This position has 0 direct reports Travel Requirements: Typically requires overnight travel 5% to 20% of the time. Physical Requirements: Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions, there may be a need to move or lift light articles. Working Conditions: Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable. Minimum Qualifications: Must be 18 years of age or older. Must be legally permitted to work in the United States. Preferred Qualifications: Bachelors or Masters in a quantitative field (Analytics, Computer Science, Math, Physics, Statistics, Management, etc.) or relevant work experience Ability to stich and maintain data from multiple sources Ability to use JavaScript, Front-end development frameworks (React, Nucleus), and QA apps (Retina, KPI Shield, Alert Goose) Ability to produce tags for site data Ability to code in Python, Google BigQuery to stitch and enrich the raw data from multiple sources Ability to use PySpark, AirFlow, and DataProc to engineer and automate data flows pipelines Ability to optimize the pipelines run time and lower the cost on slots/storage consumption Ability to prioritize requests and manage a product roadmap Demonstrated expertise of how to model and mine data Demonstrated expertise of how to build and maintain data pipelines Demonstrated knowledge of the business to support future data needs and proactive data management Minimum Education: The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job. Preferred Education: The knowledge, skills and abilities typically acquired through the completion of a master's degree program or equivalent degree in a field of study related to the job. Minimum Years of Work Experience: 5 Preferred Years of Work Experience: 6 Minimum Leadership Experience: No previous leadership experience Preferred Leadership Experience: No previous leadership experience Certifications: None Competencies: Action Oriented Collaborates Communicates Effectively Customer Focus Develops Talent Drives Engagement Drives Results Manages Conflict