Data Lead

Role & responsibilities

Develop Enterprise Data Strategy

• Define and execute the enterprise data strategy supporting portfolio governance, business intelligence and executive decision-making.
• Build a scalable data architecture that integrates information from multiple sources into a trusted reporting ecosystem.
• Standardize business definitions, KPI methodologies, and data governance across functions.

Build Portfolio Intelligence

• Develop portfolio intelligence frameworks, executive dashboards, and scorecards providing visibility into strategic initiatives, financial performance, resource utilization, risks, dependencies, and business outcomes.
• Establish leading indicators that proactively identify execution risks and opportunities.

Lead Data Governance

• Define enterprise data governance standards covering ownership, quality, integrity, stewardship, lifecycle management, and reporting controls.
• Continuously improve data quality and governance practices to ensure trusted executive reporting.

Enable Workforce and Resource Intelligence

• Build analytical models for workforce planning, capacity forecasting, demand management, resource allocation, utilization, and operational efficiency.
• Partner with PMO, and program manager to optimize workforce investments and support strategic planning.

Drive Executive Decision Support

• Translate complex business data into actionable executive insights that support portfolio prioritization, investment decisions, and operational planning.
• Identify trends, risks, dependencies, bottlenecks, and opportunities, providing recommendations that enable proactive decision-making.

Partner Across the Enterprise

• Collaborate with Strategy, Finance, Operations, Technology, Product, Resource Management, and Program teams to align enterprise reporting, analytics, and business metrics.
• Serve as the strategic data partner supporting executive governance and cross-functional decision making.

Advance Analytics and AI

• Partner with data science and engineering teams to develop predictive analytics, forecasting models, scenario planning, and AI enabled insights.
• Evaluate emerging analytics technologies and promote modern data practices that strengthen business intelligence.

Modernize Reporting and Analytics

• Design scalable reporting architectures that automate reporting, enable self-service analytics, and improve executive visibility.
• Standardize dashboards, reporting methodologies, and visualization practices to ensure consistency, accuracy, and timeliness.

Build Organizational Data Capability

• Establish repeatable governance frameworks, metadata standards, reporting templates, and documentation that improve organizational data maturity.
• Mentor analysts and promote a culture of data-driven decision making across the organization.

Preferred candidate profile

• 10+ years of progressive experience in Data Strategy, Business Intelligence, Analytics, Business Operations, Portfolio Management, Data Governance, or Management Consulting within a global technology or SaaS organization.
• Bachelor's degree in Engineering, Computer Science, Information Systems, Business Analytics, Statistics, Mathematics, Economics, or a related discipline; Master's degree or MBA preferred.
• Proven experience designing enterprise reporting architectures, executive dashboards, and business intelligence solutions.
• Strong expertise in enterprise data governance, master data management, and data quality frameworks.
• Experience supporting executive decision-making through advanced analytics and strategic reporting.
• Demonstrated success working with Director, VP, and Executive-level stakeholders.
• Strong understanding of portfolio management, workforce planning, resource management, financial reporting, and business operations.
• Experience with Azure, Snowflake, Databricks, Microsoft Fabric, or modern cloud analytics platforms.
• Advanced expertise in Power BI, SQL, Excel, and enterprise visualization tools.
• Experience working with enterprise platforms such as Salesforce, Workday, SAP, Oracle, Microsoft Dynamics, ServiceNow, Anaplan, or similar business systems.
• Experience collaborating with Data Engineering and Data Science teams to deliver scalable analytics solutions.
• Working knowledge of AI-powered analytics, predictive modeling, and modern business intelligence platforms.
• Strong commercial acumen with the ability to translate data into strategic business recommendations.
• Excellent executive communication skills with the ability to simplify complex analytical concepts for senior business leaders.
• Experience leading cross-functional analytical initiatives within highly matrixed organizations.