Sr Manager, Solutions Engineering

About this role

With a career at The Home Depot, you can be yourself and also be part of something bigger.

Position Purpose: The Solutions Engineering Sr. Manager sits between analytics engineering and application engineering, leading a team of analytics and solutions engineers (individual contributors, technical experts, and/or people managers) who build and evolve the data pipelines and self-service analytics the business relies on, and harden prototype applications into dependable solutions. This role balances the rigor of building lasting, trustworthy data and applications with the business's need for speed, partnering with platform teams to bring solutions into a supported environment. As a Solutions Engineering Sr. Manager, you will provide executive summaries to business leadership and translate strategy into execution for your team. These responsibilities require strong communication skills, relationship-building across technical and business stakeholders, and enough analytics, engineering, and business proficiency to deliver solutions the organization can rely on.

Key Responsibilities: • 50% People Management & Team Leadership - Provide leadership, mentorship and coaching to direct reports and evaluate performance, execution, and contribution; Support Data Science Director in establishing a clear vision for the team and influencing reach with business partners; Attract, retain and develop top talent to build an effective and high performing teams; Support team in development of business knowledge and technical skills with clear plans and regular assessment of progress; Develop onboarding and training plan for both technical and soft skills that will ensure high level of capabilities within the team; Foster collaboration and alignment between different data science roles to develop a supportive and engaged team; Ensure best practices and world-class techniques are leveraged in the solutioning for business problems and future team reach; Drive team's results and celebrate accomplishments • 15% Program Management - Prioritize and assign projects by striking a balance between a variety of factors, like funding, return on investment, innovative or challenging work, among others; Manage programs for the team to ensure consistency of execution, balance of resources and quality solutions; Collaborate with program managers and business partners to align on objectives and expectations and ensure project teams deliver against them; Serve as escalation point for any issues or difficulties with specific projects; Provide executive updates to leaders at all levels of the organization on program effectiveness, team accomplishments, summary of findings and recommended solution, and explain internal and external impacts; Be a champion and advocate for the team's capabilities, expertise, and needs • 25% Strategy & Business Development - Leverage extensive business knowledge and relationships to seek out new business opportunities to leverage data science and advocate for team's skills; Effectively develop trust and collaboration with internal customers and cross-functional teams; Ensure alignment with IT support model, collaboration, tools and governance to enable data scientists to be most effective in executing their roles; Collaborate with other data science managers across the organization to lead the efforts of developing high level strategy and optimizing talent management • 10% Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Ensure best practices and vision for data analysis and model productionalization are leveraged

Direct Manager/Direct Reports: • This position reports to Director or above • This position has Direct Reports and manages programs

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 eighteen years of age or older. • Must be legally permitted to work in the United States. • Demonstrated proficiency in predictive modeling, data mining and data analysis • Proficient managing and growing team members in a professional setting • Proficiency in guiding more junior team members through Data Science fundamentals in a professional setting • Demonstrated experience with translating high level strategy to tactical execution

Preferred Qualifications: • 11+ years of experience spanning data engineering, analytics engineering, or application engineering  • Previous people or project team management experience.  • Demonstrated experience refactoring or hardening prototype data products or applications into secure, reliable, production-quality solutions.  • Demonstrated experience designing and maintaining tested, version-controlled data models or transformations (e.g., Dataform, dbt), preferably against Google BigQuery or SQL.  • Experience with modern engineering practices — version control, automated testing, and deployment pipelines — applied to data or application code.  • Experience partnering with platform, infrastructure, or security teams to move data products or applications into a supported, sanctioned environment.  • Familiarity with generative AI-enabled analytics or self-service business intelligence tools

Minimum Education: • The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degr

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