Senior Manager, Big Data and Analytics

Senior Manager, Big Data and Analytics

Description -

Job Summary
• The Senior Manager, Big Data and Analytics is responsible for turning big data telemetry, customer, and product data into trusted business metrics, executive reporting, forecasting support, and actionable business insights. This role owns the delivery and modernization of analytics data products, partners across business and technology teams, and drives improvements in data platforms, automation, cost efficiency, and AI-enabled analytics workflows.

Responsibilities
• Lead delivery of key reports, dashboards, metrics, and insights for Print Supplies executive leadership, business stakeholders and partners.

• Own and improve large-scale telemetry and analytics pipelines that support installed base, usage, share, and forecasting metrics.

• Translate complex business questions into clear analytical approaches, trusted metrics, and practical recommendations.

• Partner with Print GBU, HW, CO, Finance, TIO, and Corporate teams to prioritize work and resolve cross-functional data needs.

• Lead modernization of analytics platforms, including Databricks Lakehouse, Power BI, QlikSense, pipeline automation, and cost optimization.

• Drive change management for major metric and platform updates, ensuring stakeholders understand business impact and timing.

• Improve big data monthly build processes, validation, documentation, and handoffs to increase reliability and reduce manual effort.

• Identify opportunities to apply AI, GenAI, and automation to improve analytics productivity, reporting quality, and insight generation.

• Manage intake, prioritization, and team capacity across multiple concurrent workstreams.

• Lead, coach, and develop a matrixed team of analysts, data engineers, and BI professionals, with focus on cross-training, backup planning, and career growth.
• Implement organizational practices for staffing, diversity, performance management, career development, training, reward and recognition, and retention.

Success Measures

• Reliable delivery of trusted business metrics and executive reporting.

• Improved speed, accuracy, and automation of monthly analytics processes.

• Reduced data cost and technical debt.

• Better stakeholder confidence in telemetry, forecasting, and reporting outputs.

• Stronger team resilience through documentation, cross-training, and backup coverage.

• Increased adoption of AI and modern analytics tools across the team.

Education & Experience Recommended
• Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, or any other related discipline or commensurate work experience or demonstrated competence.
• Typically has 10+ years of job-related experience or 8-10 years of management experience, preferably in data analytics, business intelligence, data engineering, or insights.

• Strong experience with big data platforms, telemetry data, SQL-based analytics, dashboarding, and data pipeline operations.

• Experience with tools such as Databricks, PowerBI, QlikSense, cloud storage, or similar modern analytics platforms.

• Strong business judgment and ability to connect data, metrics, and insights to business decisions.

• Proven ability to lead cross-functional initiatives with technical teams and senior business stakeholders.

• Strong communication skills, with ability to explain complex data or platform issues in simple business terms.

Preferred Qualifications
• Experience supporting key business stakeholders and partners with analytics and insights.

• Experience with AI-enabled analytics tools or Agentic AI workflow transformation.

• Experience leading platform migration, dashboard consolidation, cost optimization, or reporting automation.

• Strong background in change management, stakeholder alignment, and capacity-based prioritization.

Knowledge & Skills
• Agile Methodology
• Business Intelligence
• Computer Science
• Dashboard
• Data Analysis
• Data Management
• Data Modeling
• Data Quality
• Data Science
• Data Visualization
• Data Warehousing
• Extract Transform Load (ETL)
• Machine Learning
• Power BI
• Python (Programming Language)
• R (Programming Language)
• SAS (Software)
• SQL (Programming Language)
• Statistics
• Tableau (Business Intelligence Software)

Cross-Org Skills
• Customer Centricity
• Prioritization
• Resilience
• Team Management
• Strategic Thinking

Impact & Scope
• Impacts large functions and leads projects requiring knowledge of multiple disciplines or areas of HP.

Complexity
• Uses managerial concepts and company ob