Senior Manager, Reporting & Data Analytics

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Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions.

The Senior Manager, Reporting & Data Analytics oversees efforts to contribute to the definition of conceptual and logical architecture specifications (e.g., data architecture, application architecture, technical architecture) for the enterprise; directs enterprise efforts to define architecture standards that are aligned with business goals, IT strategy and enterprise architecture visions.
Also, develops overall technology architectural direction for IT’s technology portfolio, defines target state blueprints for business, application and technology architecture.
 

Primary Responsibilities

• Ensure compliance with security policies, data governance standards, and access management
• Lead development of dashboards, reports, and visualizations using Power BI, Qlik, and other products
• Develop strong relationships & partner with functional areas like product, data science, engineering, business operations, supply chain, category managers to drive initiatives
• Obtain alignment from relevant business partners and management support for projects and lead discussions to drive change
• Effectively organize, assemble, and use all available resources when given a project to ensure success
• Lead the design, build and optimization of the finance data warehouse, with a focus on structuring financial data for advanced analysis and insights
• Collaborate with cross-functional teams (Finance, Tech, Business Intelligence, etc.) to build and maintain finance data models, dashboards, and reports that meet business and reporting needs
• Guide the development of self-service analytics tools and dashboards, empowering business units to generate insights independently
• Drive the development of advanced analytical capabilities such as predictive modeling, trend analysis, AI and financial forecasting
• Leverage finance system knowledge to ensure seamless integration of financial data from ERP systems, sub-ledgers and other enterprise sources
• Collaborate with FP&A, Pricing and other Finance teams to champion a culture of data-driven decision making by providing education, support and tools
• Establish and enforce strong data governance standards to ensure high-quality, consistent, accurate and secure financial data
• Develop and deploy advanced financial reporting and analytics tools, enabling senior leadership to make informed decisions
• Manage a team of data engineers providing mentorship, guidance and support for career development
• Facilitate Business and Technology discussions at various leadership levels to build technology roadmaps to ensure alignment towards long term finance objectives
• Share your passion for staying on top of tech/industry trends, experimenting with, and learning recent technologies, participating in internal and external technology communities, and mentoring other members of the engineering community

Minimum Required Skills and Experience

• Bachelor’s degree in Engineering or Finance fields
• 10+ years of experience in quantitative or process improvement roles, using data analytics, mining, and/or visualization to solve problems
• 7-8 years of working knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
• 7-8 years of experience in aggregating and analyzing data spanning multiple sources, experience with business intelligence tools
• At least 6-7 years of experience hiring and leading a high-performance team

Preferred Qualifications

• Master’s degree in Business, or related discipline
• History of developing and implementing creative solutions for improved efficiency and effectiveness in an ambiguous, fast-paced environment
• Business focus and professional demeanor; High bias for action and passion for rolling up sleeves and doing what it takes to “get it done”
• Working knowledge of AI and it’s use in Data Analytics

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