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Amazon’s AWS Infrastructure Services in EMEA seeks a BI Engineer / Data Scientist to join the DCCD team. You will design real-time dashboards, build ETL pipelines from Procore, BIM 360, Smartsheet, and AWS data stores, and develop AI-powered insights using Bedrock and GenAI.
Collaboration with construction managers and leadership is essential. You will lead data engineering, analytics, and reporting efforts to improve schedule, cost, quality, and risk visibility across multiple regional
Description
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. The EMEA Data Center Capacity Delivery (DCCD) team is seeking a highly motivated and technically skilled Business Intelligence Engineer / Data Scientist / AI Specialist to join our Business and Project Controls function. This is a pivotal role at the intersection of construction delivery, data engineering, and artificial intelligence - supporting the EMEA DCCD team in transforming how we plan, monitor, and control the delivery of hyperscale data center capacity across the region.
You will work closely with Construction Managers, Program Managers, Technical Infrastructure Program Managers (TIPMs), and regional leadership to design and deploy intelligent data solutions that provide real-time visibility into project performance, cost, schedule, quality, and risk. You will be the data and AI engine behind our project controls function - turning raw construction data into actionable insights that drive faster, smarter, and more consistent delivery decisions.
This is an individual contributor role embedded within the EMEA DCCD Business and Project Controls team, reporting to the EMEA DCCD Business & Project Controls Lead.
Design, develop, and maintain scalable, automated dashboards and reporting systems that provide real-time visibility into EMEA DCCD project performance across cost, schedule, quality, and safety dimensions
Build and maintain BI solutions using Amazon QuickSight, Power BI, or equivalent platforms, tailored to the needs of Construction Managers and senior leadership
Develop leading indicator metrics and KPI frameworks that enable proactive risk identification and data-driven decision-making across the EMEA construction portfolio
Serve as the primary liaison between the Business & Project Controls function and technical data teams, ensuring reporting solutions are aligned to operational needs and business objectives
Produce regular programme-level performance reports and executive summaries, consolidating data from multiple projects and clusters across the EMEA region
Build and maintain robust ETL pipelines to ingest, transform, and integrate construction cost, schedule, and quality data from platforms including Procore, BIM 360, Smartsheet, and internal AWS data systems
Design and manage data models and warehousing solutions that support automated reporting and longitudinal trend analysis across the EMEA portfolio
Ensure data integrity, accuracy, and consistency across all reporting systems, establishing data governance standards and best practices within the project controls function
Develop and maintain data pipelines using Python, SQL, and AWS services (S3, Lambda, Glue, Redshift, DynamoDB) to support scalable and repeatable analytics workflows
Architect and deploy AI-powered applications using Amazon Bedrock, LLMs, and GenAI capabilities to automate and enhance construction project controls processes, including:
Build and operationalise machine learning models that extract insights from unstructured project documentation, enabling intelligent search, classification, and anomaly detection
Integrate AI capabilities with existing construction technology platforms to create seamless, automated workflows that reduce manual effort and improve data quality
Support the Business & Project Controls function in gathering, consolidating, and analysing data across EMEA clusters to produce accurate reporting on scope, schedule, budget, resources, quality, and risk
Develop and maintain construction project control dashboards that integrate traditional project management metrics with AI-generated predictive analytics
Identify gaps in current reporting and process workflows; design and implement intelligent automation solutions to eliminate non-value-add activities and reduce level of effort (LOE) on repetitive tasks
Contribute to the development and continuous improvement of project controls standards, templates, SOPs, and processes across the EMEA DCCD team
Communicate complex data findings and AI-generated insights clearly and concisely to both technical and non-technical audiences, including senior leadership
Drive adoption of new BI tools, AI solutions, and data-driven workflows across the EMEA Construction team through training, documentation, and hands-on support
Collaborate with global counterparts in AMER and APJC to share best practices, align on data standards, and scale successful solutions across AWS's global construction portfolio
Champion a culture of data-driven decision-making within the EMEA DCCD Business & Project Controls function
You will start your day reviewing automated project performance dashboards you have built, identifying any anomalies or risk signals that require attention. You will work with Construction Managers and TIPMs to understand their data needs and translate those needs into scalable reporting and AI solutions. You will spend time developing and refining ML models, building ETL pipelines, and deploying new AI-powered features on Amazon Bedrock. You will present insights to programme leadership, using data to tell a clear story about where the portfolio stands and where risks are emerging. You will collaborate with peers across the global DCCD network to align on data standards and share solutions that can be scaled across regions.
Experience in technical product or program management
Experience building and evaluating system-level technical design
Bachelor's degree in Computer Science, Computer Engineering, Data Science, Information Systems, or related STEM fields, or experience from a technical internship
Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
Experience with reporting and Data Visualization tools such as Quick Sight / Tableau / Power BI or other BI packages
Experience building data pipelines or automated ETL processes
Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS
Experience communicating complex information and solutions to senior stakeholders and influencing decisions, or experience communicating results to senior leadership
5+ years of experience in business intelligence, data engineering, or data science roles, with demonstrated ability to build and deploy production-grade reporting and analytics solutions
Proficiency in Python for data processing, automation, and machine learning model development
Experience working with construction technology platforms such as Procore, BIM 360, Smartsheet, or similar project management and document management systems
Master's degree in Data Science, Computer Science, Engineering, or related field
Experience developing AI-powered applications using LLMs and GenAI platforms (Amazon Bedrock, Claude, or similar), including agentic workflow design and prompt engineering
Experience with multimodal AI (AI Vision) for document validation, drawing compliance, or image-based quality monitoring
Experience with machine learning operations (MLOps) and deploying ML models in production environments using AWS SageMaker or equivalent
Familiarity with construction project controls methodologies including cost management, schedule analysis (Earned Value Management), and risk management
Experience with BIM information management and digital delivery standards (ISO 19650 or equivalent)
Proficiency in advanced analytics using statistical packages such as R, SAS, or equivalent
Experience with serverless architectures and infrastructure-as-code (AWS CloudFormation, CDK)
Experience developing and presenting business case analysis to senior leadership, including ROI analysis for technology and AI/ML initiatives
Demonstrated track record of delivering measurable efficiency gains through data and technology adoption on large-scale infrastructure or construction programmes
Experience working in Agile/Scrum environments and driving digital transformation initiatives
Familiarity with data governance frameworks and best practices for ensuring data integrity and accuracy in large organisations
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