[Hiring] Senior Manager of Data and Analytics @GPRS

Role Description

The Senior Manager of Data and Analytics is responsible for leading the organization's data strategy, analytics, engineering, business intelligence, and AI-enablement initiatives. This role serves as the bridge between business leaders and technical resources, translating complex business questions into actionable insights, scalable data solutions, and measurable operational improvements.

• Transform the organization into a data-empowered enterprise by delivering trusted insights, governed data assets, and self-service analytical capabilities.
• Build and scale a modern data platform that supports reporting, analytics, forecasting, AI initiatives, and enterprise decision making.
• Drive measurable business performance improvements through advanced analytics, operational optimization, KPI management, and proactive identification of opportunities across the organization.

Qualifications

• Bachelor's degree in Data Analytics, Computer Science, Information Systems, Engineering, Mathematics, Statistics, Economics, or a related field.
• 7+ years of experience in analytics, business intelligence, data engineering, data science, or related disciplines.
• 3+ years of experience leading teams, projects, or enterprise initiatives.
• Advanced proficiency in SQL and data analysis.
• Strong experience with Python or similar analytical programming languages.
• Experience designing and supporting data warehouses, lakehouses, and enterprise reporting environments.
• Experience developing executive dashboards and KPI frameworks.
• Strong understanding of ETL/ELT processes, data modeling, and data governance principles.
• Demonstrated ability to communicate complex analytical concepts to both technical and non-technical audiences.
• Proven ability to drive projects from problem definition through implementation and measurement.

Requirements

• Lead, mentor, and develop data analysts, data engineers, and AI engineers.
• Define quarterly and annual roadmaps for data, analytics, and AI initiatives.
• Prioritize team initiatives and align resources against organizational objectives.
• Balance tactical reporting requests with long-term strategic initiatives.
• Establish standards for analytics development, data governance, documentation, testing, and deployment.
• Drive accountability for project execution, delivery timelines, and business outcomes.
• Partner directly with executive leadership and business unit leaders to solve complex business problems.
• Translate ambiguous business questions into analytical investigations and actionable recommendations.
• Perform deep quantitative and qualitative analysis to identify operational, financial, customer, and market opportunities.
• Present findings and recommendations to senior leadership in a clear and concise manner.
• Evaluate organizational performance and recommend solutions to improve efficiency, effectiveness, and profitability.
• Proactively identify areas for analysis without waiting for formal requests.
• Develop frameworks and methodologies for measuring business performance.
• Own organizational KPI definitions, governance, and reporting standards.
• Build and maintain executive dashboards and operational reporting solutions.
• Conduct advanced analyses related to productivity, labor utilization, scheduling optimization, sales performance, customer experience, revenue growth, margin improvement, and operational efficiency.
• Develop forecasting, trend analysis, and predictive analytics capabilities.
• Provide ongoing performance monitoring and actionable recommendations based on data.
• Guide development of enterprise data warehouse and lakehouse environments.
• Oversee data pipeline design, ETL/ELT processes, data integration, and data quality initiatives.
• Support master data management and enterprise data governance efforts.
• Design scalable data models that support reporting, analytics, AI, and future growth.
• Establish standards for data architecture, quality, documentation, lineage, and stewardship.
• Ensure reliability, accuracy, accessibility, and scalability of enterprise data assets.
• Partner with business and technology leaders to identify and prioritize AI opportunities.
• Lead initiatives that enable conversational analytics, intelligent agents, automation, and AI-driven decision support.
• Support development of semantic models, business metadata layers, and governed datasets that improve AI effectiveness.
• Evaluate emerging technologies and recommend innovative approaches to improve organizational performance.
• Help define the long-term roadmap for enterprise analytics, data science, and AI capabilities.

Benefits

• Full medical, dental, and vision insurance with day-one coverage.
• 401k with company matching beginning on day one.
• Life, Short-Term, and Long-Term Disability at no cost to employees.
• Paid holidays and paid time off.
• Leadership development training programs.
• Additional benefits to support the development of each team member.