Asks for

The ad says“BMS/SCADA data platforms and energy monitoring systems”
The ad says“Strong knowledge of Critical infrastructure (electrical, mechanical, cooling, generators, UPS)”
The ad says“Good understanding of energy management standards and KPI frameworks (PUE, WUE, CUE, EnPI, GHG)”
The ad says“Proven experience in energy data analysis, KPI modelling and performance management in a multi-site environment.”
The ad says“Good understanding of energy management standards and KPI frameworks (PUE, WUE, CUE, EnPI, GHG)”
The ad says“BMS/SCADA data platforms and energy monitoring systems”
The ad says“Good understanding of energy management standards and KPI frameworks (PUE, WUE, CUE, EnPI, GHG)”
The ad says“Good understanding of energy management standards and KPI frameworks (PUE, WUE, CUE, EnPI, GHG)”
The ad says“Monitoring and data visualization tools (e.g., Grafana)”
The ad says“Good understanding of ISO 50001 and familiarity with understanding of ISO standards (9001, 14001, 45001, 27001)”
The ad says“Good understanding of ISO 50001 and familiarity with understanding of ISO standards (9001, 14001, 45001, 27001)”
The ad says“Good understanding of ISO 50001 and familiarity with understanding of ISO standards (9001, 14001, 45001, 27001)”
The ad says“Good understanding of ISO 50001 and familiarity with understanding of ISO standards (9001, 14001, 45001, 27001)”
The ad says“Good understanding of ISO 50001 and familiarity with understanding of ISO standards (9001, 14001, 45001, 27001)”
The ad says“Proven experience in energy data analysis, KPI modelling and performance management in a multi-site environment.”
The ad says“Measurement & Verification (M&V) methodologies for energy project assessment”
The ad says“Proven experience in energy data analysis, KPI modelling and performance management in a multi-site environment.”
The ad says“Good understanding of energy management standards and KPI frameworks (PUE, WUE, CUE, EnPI, GHG)”
The ad says“Root cause analysis and structured problem-solving methodologies”
The ad says“Root cause analysis and structured problem-solving methodologies”
The ad says“Good understanding of energy management standards and KPI frameworks (PUE, WUE, CUE, EnPI, GHG)”

DATA4'S MISSION

Building highly connected, resilient and responsible Data Center campuses to support the growth of our customers in Europe. DATA4 is a major European operator and investor in the Data Centers market. The Group finances, designs, builds and operates its own data centers.

DATA4 VALUES

At DATA4 we are driven by our values. These are the core of everything we do:

Initiative – We foster a culture of ownership, autonomy, and proactive execution to deliver clear and measurable results.
Responsibility – We act with integrity and accountability, ensuring sustainable, transparent, and responsible operations.
Adaptability – We embrace change and continuously evolve our operating models to anticipate future challenges and opportunities.

About the Role

The Energy Efficiency Engineer is responsible for providing the analytical and technical backbone of the group's energy performance management. The role designs and maintains predictive models for energy KPIs, validates data from monitoring systems, supports root cause analysis on significant deviations and assesses the feasibility of energy efficiency initiatives. The Energy Data & Performance Specialist ensures that energy reports are technically sound and consistent before internal and external distribution, acting as the primary technical reference across all countries in scope.

The role reports directly to the Energy & Resource Operation Manager and operates in a transversal and highly collaborative environment, working closely with Country Operations Directors, Global Operations Team, Finance, IT and Compliance teams to ensure alignment and execution of group-level initiatives.

The position can be based in Cornaredo (Italy) or Alcobendas (Spain)

KEY RESPONSIBILITIES

Energy KPI Modelling & Forecasting

Design, develop and maintain predictive models for group energy KPIs (PUE, WUE, CUE, ERF, REF, EnPIs), incorporating relevant variables (such as weather-normalised data, IT load and seasonal patterns, etc.)
Own the definition and periodic update of Energy Baselines (EnB) and Energy Performance Indicators (EnPIs), ensuring full methodological traceability across all sites.
Drive the continuous improvement of modelling accuracy, integrating operational feedback from site teams and updating assumptions following significant changes in infrastructure or workload.
Produce periodic forecasting reports and present findings to the Energy & Resource Operation Manager and relevant stakeholders.

Energy Data Validation & Monitoring

Support country teams in identifying, defining, and validating the critical energy parameters required for energy analyses and reporting, ensuring data quality and consistency across monitoring systems (BMS, Databases, Grafana) before data enters reporting flows.
Support site OPS teams in the interpretation of monitoring parameters, providing technical guidance on data reliability and measurement correctness.
Define and maintain alarm thresholds and anomaly detection logic across all monitored energy parameters, ensuring early identification of performance drifts.
Coordinate with IT and BMS teams to resolve data integration issues and ensure continuity and accuracy of energy data flows into central repositories.

Root Cause Analysis & Energy Review

Provide technical guidance to country teams in the investigation of significant energy deviations, supporting the development of structured root cause analyses with quantified impact assessment and identification of contributing factors.
Support country teams in defining corrective and preventive action plans (CAPA) following RCA findings, providing methodological guidance and monitoring effectiveness over time at group level.
Support country teams in conducting periodic Energy Reviews, providing the analytical framework and technical expertise needed to identify and update Significant Energy Uses (SEUs) in response to operational changes across all sites.

Energy Project Feasibility & Report Validation

Support country teams in the technical and economic assessment of energy efficiency initiatives (CAPEX/OPEX), providing the analytical methodology and M&V framework needed to produce structured business cases.
Provide technical input to support the prioritisation of the energy improvement roadmap, translating site-level data into quantified impact and effort assessments.
Review monthly and quarterly energy reports produced by country teams, ensuring consistency between raw operational data, calculated KPIs and disclosed figures before internal and external distribution.

Requirements:

Bachelor’s or master’s degree in engineering (Industrial or Energy) or equivalent
Specialised training or certification in energy data analysis, statistics or modelling is a plus
Minimum 3 years of experience in critical infrastructure, data centers, or industrial operations
Proven experience in energy data analysis, KPI modelling and performance management in a multi-site environment.
Good understanding of energy management standards and KPI frameworks (PUE, WUE, CUE, EnPI, GHG)
Good understanding of ISO 50001 and familiarity with understanding of ISO standards (9001, 14001, 45001, 27001)
Fluent English
Travel required in Europe (once per month)

Technical Skills

Strong knowledge of Critical infrastructure (electrical, mechanical, cooling, generators, UPS)
Experience with:
- Monitoring and data visualization tools (e.g., Grafana)
- KPI frameworks and performance management
- BMS/SCADA data platforms and energy monitoring systems
- Measurement & Verification (M&V) methodologies for energy project assessment
- Root cause analysis and structured problem-solving methodologies

General Skills

Strong analytical mindset, methodological rigour and attention to data quality.
Ability to translate complex technical findings into clear, actionable insights for both technical and non-technical stakeholders.
Structured approach to problem-solving, with the ability to manage multiple analytical workstreams simultaneously.
Proactive attitude towards continuous improvement of data quality, modelling accuracy and reporting standards.

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