Global Data & Analytics Manager DE&C

Your role

The role of the Global Design Engineering & Construction (DE&C) Data & Analytics Manager is essential in upholding data-driven excellence across global construction projects. This role focuses on developing and executing comprehensive global data management and analytics strategy including rigorous data quality assurance across multiple ERP systems consolidation of information sources advanced analytics and executive-level reporting. The ideal candidate will enable teams to control and transform raw data into actionable insights supporting informed decision-making at global portfolio regional and subregional levels. This individual will champion innovation in data practices and ensure efficiency by aligning analytical ways of working globally.

The Global DE&C Data & Analytics Manager will be a multi-disciplinary enthusiastic and proactive professional with exceptional analytical organizational and presentation skills confident in interacting with internal stakeholders across multiple levels and functions. Requiring strong technical expertise in data science and analytics as well as a solid understanding of construction project operations this role supports ongoing delivery and innovation through data-driven decision-making in a complex multi-layered global matrix environment.

What youll do

Global Data Strategy & Governance:

Develop and Implement Data Strategy: Define and execute a global data management and analytics strategy for DE&C aligning with organizational objectives and project delivery needs. Establish a clear vision for how data is used to drive decisions across all construction projects.

Data Governance: Create and enforce global data governance standards policies and best practices to ensure data consistency quality and integrity across multiple systems and regions. Set up guidelines for data usage security and sharing maintaining compliance with internal and external requirements.

Standardization: Define and maintain data taxonomies templates and definitions to standardize information across various projects and regions enabling apples-to-apples comparisons and coherent reporting. Ensure that all regional and functional teams adhere to common data definitions and metrics.

Policy and Best Practice Leadership: Have the authority to establish and propagate best practices in data handling and analytics. Continuously refine the governance framework to adapt to new challenges tools or business requirements ensuring that data practices remain cutting-edge and effective globally.

Workflow Improvement: Analyze existing workflows related to data collection reporting and analytics within DE&C. Identify inefficiencies or pain points (like duplicate data entry or slow report turnaround times) and redesign processes to be more streamlined and user-friendly.

Return on Investment (ROI) and Value Tracking: Assess and communicate the business impact of data initiatives. Track efficiency gains or cost savings resulting from improved analytics (for instance hours saved by automation better budgeting accuracy or avoidance of risk events due to early warning from data). Use these metrics to justify further investment in analytics and to focus efforts on the highest-value activities.

Documentation and Knowledge Management: Ensure all data processes models and key insights are well-documented. Maintain a repository of analytical methods business rules and past analyses so the organization builds a memory and new team members can get up to speed quickly. Documenting also supports auditability and knowledge transfer within the team.

Data Integration Quality Management and Consolidation:

Cross-Platform Data Integration: Oversee the consolidation of data from diverse sources and Enterprise Resource Planning (ERP) systems (finance project management etc.) into a central repository or data lake. Ensure seamless integration of data from various business units and functional areas (e.g. Commercial Operations Finance Procurement) for a holistic view of project performance.

Data Cleaning and Quality Control: Lead initiatives to clean and harmonize data across systems identifying discrepancies resolving data quality issues and establishing processes for continuous data quality improvement. Implement data validation checks and automate data cleaning where possible to maintain a high degree of accuracy and trust in the data.

Single Source of Truth: Work towards creating a single source of truth for DE&C project data globally. This includes designing data architectures or leveraging existing platforms to centralize information making it easily accessible and reliable for stakeholders at all levels.

Tool and System Optimization: Collaborate with IT and software teams to improve data pipelines and system integrations. Influence the selection and implementation of data management tools or platforms (such as data warehouses ETL tools or integration middleware) that will facilitate efficient data consolidation and retrieval. Data Governance Tools: Deploy and manage data catalogues or other governance tools that document data sources lineage and definitions. This ensures transparency in where data comes from and helps users understand and trust the information provided

Reporting Performance Tracking and Data Insights:

Advanced Analytics & AI Integration: Leverage advanced analytics techniques including statistical analysis predictive modeling and AI/ML integrations to extract deeper insights from project data. Identify trends correlations and leading indicators that can inform proactive decision-making (e.g. predicting project delays or cost overruns before they happen using data patterns).

Dashboarding and Reporting: Lead the design and development of executive-level dashboards and reports that provide clear visibility into project and portfolio health. Use business intelligence tools primarily Power BI and potentially others like Tableau to create interactive and intuitive visualizations. Ensure these dashboards highlight key performance indicators (KPIs) such as cost schedule adherence risk metrics and resource utilization etc..

Insight Communication: Synthesize complex data into concise presentations and reports tailored for various audiences from executive leadership to project teams. Clearly communicate what the data is saying telling the story behind the numbers so that stakeholders can quickly grasp issues and opportunities. This includes writing commentary and briefing notes that explain findings and recommendations.

Global and Regional Analysis: Provide analytics at multiple levels global roll-ups for senior management as well as granular analysis for regional and subregional teams. Deliver insights that enable comparison between regions or projects helping identify best performers outliers and areas needing attention.

Continuous Improvement of Reporting: Continuously refine reporting tools and processes. Solicit feedback from stakeholders to improve the relevance and usability of analytics outputs. Automate recurring reports and ensure real-time data availability where possible reducing manual effort and increasing responsiveness.

Performance Tracking: Define and track operational KPIs related to project controls and execution (e.g. forecasting accuracy data timeliness reporting lag). Provide regular updates and insight into these metrics to drive accountability and improve performance across the DE&C organization.

Digital Tooling and Innovation in Analytics:

BI Tools Expertise: Act as the in-house expert on Power BI and similar analytics platforms. Champion the use of these tools across DE&C for reporting and analysis. Train and support other team members in utilizing BI tools effectively ensuring self-service analytics capabilities are developed within regional teams.

Emerging Technologies: Stay up to date with emerging technologies in data analytics AI and construction tech. Evaluate the applicability of new solutions (e.g. AI-driven analytics platforms data visualization techniques or big data tools) to continuously enhance the DE&C analytics ecosystem.

Automation: Identify opportunities for automation in data collection reporting and analysis. Implement automated data workflows and reporting pipelines to minimize manual data handling and reduce errors. For instance automate the generation of weekly project dashboards or develop alert systems that notify stakeholders of anomalies (such as cost spikes or schedule slips).

Data-Driven Culture & Tools Integration: Support the integration of analytics with existing construction management tools (such as Procore Primavera or others used in DE&C). Ensure that data flows from project management systems into analytical models smoothly. Promote a culture where project and regional teams routinely use data and tools to guide their decisions making data-driven decision-making a standard practice.

Innovation and AI Solutions: Pilot and implement AI integration where it can add value for example using machine learning to forecast project outcomes employing natural language processing (NLP) to analyze project documents or survey feedback or integrating with chatbots for querying project databases. Validate these innovations through small-scale trials and scale up successful solutions to global use

Collaboration Stakeholder Engagement and Support:

Cross-Functional Collaboration: Operate effectively in a multi-layered matrix organization. Engage with various internal stakeholders including Project Controls Regional DE&C teams Finance IT Operations and others to gather required data and drive analytics initiatives. Act as a bridge between technical data teams and construction project teams to ensure data solutions meet real-world project needs.

Primary Liaison & Training: Serve as the primary liaison for regional and project teams on all matters related to data and analytics. Provide expert guidance support and training to stakeholders to improve data literacy and the use of analytics tools. This may involve conducting workshops or one-on-one coaching sessions to help teams interpret dashboards or to input data correctly into systems.

Influence without Direct Authority: Use strong leadership and interpersonal skills to lead by influence since this is largely an individual contributor role. Champion the value of data and analytics in meetings and forums persuading teams and leaders to adopt best practices and to prioritize data quality in their operations.

Stakeholder Management: Manage expectations and requirements from a wide array of stakeholders. Balance requests for data or reports from senior leadership with the capacity and data availability from regional teams. Negotiate and align on analytics priorities ensuring that urgent needs are met while also progressing strategic data initiatives.

Global Insight Sharing: Facilitate knowledge sharing across regions. When one region uncovers a valuable insight or a best practice in analytics (for example a new way to visualize schedule risk) ensure that this knowledge is shared and potentially adopted in other regions. Foster communities of practice for data analysts within DE&C globally.

Collaborative Planning: Participate in DE&C planning sessions strategy workshops and project reviews contributing a data-driven perspective. Ensure that planning and decision forums always consider the analytical insights and that data is at the table for key discussions.

What youll need

Strong experience in data analytics data science or business intelligence with significant exposure to construction or infrastructure projects (preferably data center projects or similar large-scale capital-intensive programs). A deep understanding of construction project lifecycles and the types of data generated (schedules costs risks etc.) is highly advantageous.

Proven experience in managing and integrating data from multiple systems (such as ERPs project management software financial systems). Familiarity with common construction/engineering software (e.g. SAP Oracle Primavera Procore) and how to extract or interface data from them is preferred.

Advanced proficiency in Power BI is required including building complex dashboards writing DAX calculations and managing workspace deployments. Experience with other data visualization and reporting tools (Tableau Looker etc.) is a plus.

Strong skills in data analysis and statistical modeling. Comfortable using tools/languages such as Excel (advanced) SQL and possibly Python/R for data manipulation and analysis. Experience developing predictive models or applying machine learning in a business context (even if not coding from scratch) is beneficial especially for forecasting and trend analysis.

Good understanding of AI/ML concepts and experience integrating or leveraging AI solutions (like predictive analytics anomaly detection or AI-driven data cleaning). Knowledge of how to use or implement automation in data workflows (for example using scripts or BI tool features to auto-refresh and distribute reports).

Demonstrated experience working in a complex global organization. Comfortable navigating a matrix structure with cross-functional teams. Experience coordinating initiatives across different regions or departments and adapting to cultural and operational differences.

A solid grasp of project controls fundamentals (schedule cost risk management) and how data underpins these areas. While this is a data role understanding the basics of project management and controls ensures that analytics align with real project needs and speak the language of project teams.

Experience in continuous process improvement related to data or reporting. Has defined and tracked metrics/KPIs to measure performance improvements over time. Ideally experience with methodologies like Six Sigma Lean or similar in the context of data processes although not mandatory.