Data Manager

JOB OVERVIEW
The Data Manager is responsible for leading the organization's data and business intelligence strategy, ensuring the delivery of accurate, timely, and actionable insights to support strategic decision-making. This role oversees the development of a Single Source of Truth, manages data infrastructure, and drives data governance and analytics initiatives. The Data Manager acts as a strategic partner to business leaders, transforming data into business value while mentoring and developing the BI and Data Engineering teams.
Reports To: Head of IT
KEY RESPONSIBILITIES
1. Leadership & Team Management
• Lead, mentor, and develop a team to ensure high performance and continuous growth.
• Define team objectives, KPIs, and workflows aligned with organizational goals.
• Allocate resources and prioritize analytics initiatives across different business squads.
• Foster a data-driven culture and promote collaboration between technical and business teams.
• Conduct performance evaluations and support career development plans.
2. Data Strategy & Governance
• Define and execute the company's data strategy aligned with business objectives.
• Establish and maintain a Single Source of Truth for all business metrics.
• Develop and enforce data governance policies, standards, and best practices.
• Build and maintain data dictionaries, documentation, and standardized KPI definitions.
• Ensure data quality, integrity, security, and compliance across all systems.
3. Business Intelligence & Analytics
• Oversee the design and delivery of interactive dashboards and executive reports for various business functions.
• Translate business questions into analytical frameworks and actionable insights.
• Conduct advanced analyses such as root cause analysis, cohort analysis, and performance optimization.
• Provide strategic recommendations to support decision-making and business growth.
• Enable self-service analytics for business users.
4. Data Engineering & Infrastructure
• Supervise the design, development, and optimization of data pipelines and ETL/ELT processes.
• Collaborate with the Data Engineer to ensure scalable and efficient data architecture.
• Support the development of data warehouses/lakes and integration of multiple data sources (CRM, ERP, Marketing platforms, APIs).
• Ensure system reliability, performance, and scalability.
5. Cross-Functional Collaboration
• Partner with Marketing, Commercial, Finance, Operations, and PMO teams to understand data needs and deliver impactful insights.
• Act as a strategic advisor to senior leadership on data-driven initiatives.
• Support forecasting, scenario planning, and performance monitoring.
• Drive continuous improvement in business processes through analytics.
6. Innovation & Continuous Improvement
• Identify opportunities to leverage advanced analytics, automation, and AI/ML.
• Stay updated with emerging trends in data management and business intelligence.
• Promote best practices in data visualization and storytelling.