📍 Job Overview

Job Title: Data Center Tools and Reporting Specialist
Company: Start Campus
Location: Lisbon, Portugal (with weekly trips to Sines) or Sines, Portugal
Job Type: Hybrid (1 day per week in the office)
Category: Data Analysis, Business Intelligence
Date Posted: 2025-07-03
Experience Level: 2-5 years
Remote Status: Hybrid

🚀 Role Summary

Key Responsibilities: Collect, clean, and validate data; analyze data to generate insights; build and maintain reports and dashboards; collaborate with internal teams to define KPIs and reporting requirements; present insights to non-technical stakeholders; support analytics initiatives; monitor and improve data quality; enhance IT tools and process flows.
Key Qualifications: Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or related field; 2-5 years of experience in data analysis, business intelligence, or similar roles; strong proficiency in SQL and at least one statistical programming language (Python or R); experience with data visualization tools such as Power BI or Tableau; analytical mindset with attention to detail and problem-solving skills; excellent communication skills; knowledge of machine learning concepts and data modelling is a plus.

📝 Enhancement Note: This role requires a strong blend of technical data skills and business acumen to turn raw data into strategic insights, enabling smarter, faster decision-making across the business. The ideal candidate will have experience working with various systems and tools, as well as the ability to collaborate effectively with cross-functional teams.

💻 Primary Responsibilities

Data Collection & Cleaning: Collect, clean, and validate data from systems such as CMMS, BMS, EPMS, CRM, ERP, and IoT platforms.
Data Analysis: Use SQL, Python, or R to analyze data, identify trends, and generate insights.
Reporting & Visualization: Build and maintain reports and dashboards using Excel, Power BI, or Tableau.
Collaboration: Work with internal teams to define KPIs and reporting requirements, and present insights in a clear, engaging way to non-technical stakeholders.
Analytics Initiatives: Support analytics initiatives such as forecasting, segmentation, and performance modeling.
Data Quality & Governance: Monitor and improve data quality, contributing to robust data governance.
IT Tools & Process Enhancement: Enhance IT tools and process flows that support reporting and data-driven decisions.

📝 Enhancement Note: The primary responsibilities of this role revolve around data management, analysis, and visualization. The ideal candidate will have a strong foundation in data analysis techniques, proficiency in relevant tools, and the ability to communicate complex data insights effectively.

🎓 Skills & Qualifications

Education: A Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or a related field is required.

Experience: A minimum of 2-5 years of experience in data analysis, business intelligence, or a similar role is necessary. Candidates with experience working in data-driven environments and collaborating with cross-functional teams are strongly preferred.

Required Skills:

Strong proficiency in SQL and at least one statistical programming language (Python or R)
Experience with data visualization tools such as Power BI or Tableau
Analytical mindset with attention to detail and problem-solving skills
Excellent communication skills, both written and verbal
Ability to work independently and manage multiple priorities in a dynamic environment

Preferred Skills:

Knowledge of machine learning concepts and data modeling
Experience with data governance and data quality management
Familiarity with data analysis tools such as Excel, Power BI, or Tableau
Ability to work with various data sources and systems

📝 Enhancement Note: While the required skills for this role are well-defined, the preferred skills section highlights areas where additional experience or knowledge would be beneficial. Candidates with experience in machine learning, data governance, and working with various data sources and systems are likely to be more successful in this role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A well-structured portfolio showcasing previous data analysis, business intelligence, or related projects.
Examples of data cleaning, analysis, and visualization techniques used in past projects.
Case studies demonstrating the ability to generate insights and drive business decisions based on data.
Live demos or interactive visualizations, if applicable, to showcase technical skills and data storytelling abilities.

Technical Documentation:

Detailed documentation of data cleaning, transformation, and analysis processes used in past projects.
Clear explanations of data sources, methods, and assumptions used in analysis and visualization.
Evidence of data quality management and governance practices in past projects.
Examples of collaboration with cross-functional teams and stakeholders, demonstrating strong communication skills.

📝 Enhancement Note: As this role focuses on data analysis and reporting, the portfolio should emphasize the candidate's ability to collect, clean, analyze, and visualize data effectively. Case studies demonstrating the impact of data-driven insights on business decisions are particularly valuable.

💵 Compensation & Benefits

Salary Range: The salary range for this role is estimated to be between €35,000 and €50,000 per year, based on market research and the candidate's experience level. This estimate takes into account the location (Lisbon, Portugal) and the required experience (2-5 years).

Benefits:

Impact: Lead world-class operations at Europe’s largest and most sustainable data center.
Collaboration: Work closely with cross-functional teams and contribute to business development.
Flexibility: Empowered to lead with autonomy and creativity in a fast-paced, client-centric environment.
Growth: Join a company committed to innovation, professional development, and service excellence.

Working Hours: The standard working hours for this role are 40 hours per week, with the expectation of working on-site one day per week.

📝 Enhancement Note: The salary range provided is an estimate based on market research and the candidate's experience level. The benefits section highlights the unique aspects of working at Start Campus, emphasizing the impact, collaboration, flexibility, and growth opportunities available to the successful candidate.

🎯 Team & Company Context

🏢 Company Culture

Industry: Start Campus operates in the data center services industry, providing mission-critical data center services that power businesses globally.

Company Size: Start Campus is a growing company, which means the successful candidate will have the opportunity to make a significant impact on the organization's growth and success.

Founded: Start Campus was founded with a commitment to innovation, professional development, and service excellence.

Team Structure:

The Operations team is responsible for managing the day-to-day operations of the data center, ensuring optimal performance and reliability.
The successful candidate will work closely with cross-functional teams, including IT, Facilities, and Business Development, to enhance process efficiency, drive data quality, and deliver impactful visualizations and reports.

Development Methodology:

Start Campus uses a data-driven approach to decision-making, with a focus on continuous improvement and innovation.
The successful candidate will be expected to collaborate effectively with cross-functional teams, using Agile methodologies to deliver high-quality results.

Company Website: Start Campus Website

📝 Enhancement Note: The company culture section provides an overview of Start Campus' industry, size, founding, team structure, and development methodology. This information helps the candidate understand the context in which they will be working and the expectations for their role within the organization.

📈 Career & Growth Analysis

Data Analysis Career Level: This role is at the intermediate to senior level within the data analysis career path. The successful candidate will be expected to have a strong foundation in data analysis techniques, as well as experience working with various data sources and systems.

Reporting Structure: The Data Center Tools and Reporting Specialist will report directly to the Operations Manager and work closely with cross-functional teams, including IT, Facilities, and Business Development.

Technical Impact: The successful candidate will have a significant impact on the data-driven decision-making processes at Start Campus. They will be responsible for turning raw data into strategic insights, enabling smarter, faster decision-making across the business.

Growth Opportunities:

Career Progression: As Start Campus continues to grow, there will be opportunities for the successful candidate to take on more responsibilities and advance their career within the organization.
Technical Skill Development: The successful candidate will have the opportunity to develop their technical skills by working with various data sources and systems, as well as collaborating with cross-functional teams.
Leadership Potential: The successful candidate will have the opportunity to develop their leadership skills by working with cross-functional teams and contributing to business development.

📝 Enhancement Note: The career and growth analysis section provides an overview of the data analysis career level, reporting structure, technical impact, and growth opportunities available to the successful candidate. This information helps the candidate understand the potential for career advancement and professional development within the organization.

🌐 Work Environment

Office Type: Start Campus offers a hybrid work environment, with employees expected to work on-site one day per week.

Office Location(s): The primary office locations are in Lisbon and Sines, Portugal.

Workspace Context:

Collaborative Workspace: The workspace is designed to foster collaboration and communication among team members.
State-of-the-Art Technology: The workspace is equipped with state-of-the-art technology, including high-speed internet, multiple monitors, and testing devices.
Cross-Functional Interaction: The workspace encourages interaction with cross-functional teams, including IT, Facilities, and Business Development.

Work Schedule: The standard work schedule is 40 hours per week, with the expectation of working on-site one day per week.

📝 Enhancement Note: The work environment section provides an overview of the office type, office locations, workspace context, and work schedule. This information helps the candidate understand the physical environment in which they will be working and the expectations for their presence in the office.

📄 Application & Technical Interview Process

Interview Process:

Initial Screening: A phone or video call to discuss the candidate's experience, skills, and career goals.
Technical Assessment: A take-home data analysis assignment or case study to evaluate the candidate's technical skills and problem-solving abilities.
Behavioral Interview: A structured interview to assess the candidate's fit with Start Campus' company culture and values.
Final Interview: A meeting with the Operations Manager to discuss the candidate's long-term career goals and the opportunity for growth within the organization.

Portfolio Review Tips:

Highlight previous data analysis, business intelligence, or related projects that demonstrate the candidate's ability to collect, clean, analyze, and visualize data effectively.
Include case studies that showcase the candidate's ability to generate insights and drive business decisions based on data.
Emphasize the candidate's ability to work with various data sources and systems, as well as their experience collaborating with cross-functional teams.

Technical Challenge Preparation:

Brush up on SQL, Python, or R skills, as well as data visualization tools such as Power BI or Tableau.
Practice data cleaning, analysis, and visualization techniques using sample datasets.
Prepare for questions about data governance, data quality management, and data-driven decision-making processes.

ATS Keywords: Data Analysis, SQL, Python, R, Data Visualization, Power BI, Tableau, Communication, Problem Solving, Data Quality, Data Governance, Forecasting, Segmentation, Performance Modeling, Machine Learning, Data Modelling

📝 Enhancement Note: The application and technical interview process section provides an overview of the interview process, portfolio review tips, and technical challenge preparation. This information helps the candidate understand the expectations for the interview process and how to best prepare for success.

🛠 Technology Stack & Web Infrastructure

Data Analysis Tools:

SQL: Used for data collection, cleaning, and manipulation.
Python or R: Used for data analysis, modeling, and visualization.
Excel: Used for data organization, analysis, and reporting.
Power BI or Tableau: Used for data visualization and reporting.

Data Sources:

CMMS, BMS, EPMS, CRM, ERP, and IoT platforms: Used for data collection and integration.

Data Storage:

Relational databases: Used for structured data storage and management.
Cloud-based data warehouses: Used for data storage, processing, and analysis.

📝 Enhancement Note: The technology stack and web infrastructure section provides an overview of the data analysis tools, data sources, and data storage solutions used at Start Campus. This information helps the candidate understand the technical environment in which they will be working and the expectations for their use of these tools and technologies.

👥 Team Culture & Values

Data Analysis Values:

Accuracy: Start Campus values accurate and reliable data analysis, ensuring that insights are based on sound data and robust methodologies.
Collaboration: Start Campus fosters a culture of collaboration, with data analysts working closely with cross-functional teams to deliver impactful insights.
Innovation: Start Campus encourages continuous learning and innovation, with data analysts staying up-to-date with the latest data analysis techniques and tools.
Impact: Start Campus values data-driven decision-making, with data analysts working to generate insights that drive business impact.

Collaboration Style:

Cross-Functional Integration: Data analysts work closely with cross-functional teams, including IT, Facilities, and Business Development, to deliver impactful insights and drive business growth.
Code Review Culture: Start Campus encourages a code review culture, with data analysts reviewing each other's work to ensure quality and consistency.
Knowledge Sharing: Start Campus fosters a culture of knowledge sharing, with data analysts collaborating to develop best practices and share expertise.

📝 Enhancement Note: The team culture and values section provides an overview of the data analysis values and collaboration style at Start Campus. This information helps the candidate understand the company's approach to data analysis and the expectations for their role within the organization.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Quality: Ensuring data accuracy, completeness, and consistency across various data sources and systems.
Data Integration: Integrating data from different sources and systems to generate comprehensive insights.
Data Visualization: Creating intuitive, engaging, and actionable visualizations that communicate complex data insights effectively.
Data-Driven Decision-Making: Developing and implementing data-driven decision-making processes that drive business impact.

Learning & Development Opportunities:

Data Analysis Techniques: Developing advanced data analysis techniques, such as machine learning, predictive modeling, and data mining.
Data Visualization Tools: Expanding proficiency in data visualization tools, such as Power BI or Tableau, to create more sophisticated and engaging visualizations.
Data Governance: Enhancing data governance skills to ensure data quality, security, and compliance with relevant regulations.
Leadership Development: Developing leadership skills to manage teams, mentor junior data analysts, and drive data-driven decision-making processes.

📝 Enhancement Note: The challenges and growth opportunities section provides an overview of the technical challenges and learning and development opportunities available to the successful candidate. This information helps the candidate understand the potential for professional growth and development within the organization.

💡 Interview Preparation

Technical Questions:

Data Analysis Fundamentals: Questions assessing the candidate's understanding of data analysis fundamentals, such as data cleaning, transformation, and manipulation techniques.
Data Visualization: Questions evaluating the candidate's ability to create intuitive, engaging, and actionable visualizations using tools such as Power BI or Tableau.
Data-Driven Decision-Making: Questions exploring the candidate's understanding of data-driven decision-making processes and their ability to generate insights that drive business impact.

Company & Culture Questions:

Company Culture: Questions assessing the candidate's fit with Start Campus' company culture and values, as well as their understanding of the organization's mission and vision.
Data Analysis Team Dynamics: Questions exploring the candidate's ability to work effectively with cross-functional teams and contribute to a collaborative, innovative, and impact-driven data analysis culture.
Data Analysis Methodologies: Questions evaluating the candidate's understanding of data analysis methodologies, such as Agile, Scrum, or Kanban, and their ability to apply these methodologies in a data-driven decision-making context.

Portfolio Presentation Strategy:

Live Demo: Presenting a live demo of the candidate's data analysis, visualization, and reporting skills using tools such as Power BI or Tableau.
Case Study: Presenting a case study that demonstrates the candidate's ability to collect, clean, analyze, and visualize data to generate insights and drive business decisions.
Technical Walkthrough: Providing a technical walkthrough of the candidate's data analysis, visualization, and reporting processes, highlighting their use of best practices and industry-standard techniques.

📝 Enhancement Note: The interview preparation section provides an overview of the technical and company and culture questions, as well as the portfolio presentation strategy. This information helps the candidate understand the expectations for the interview process and how to best prepare for success.

📌 Application Steps

To apply for this Data Center Tools and Reporting Specialist position at Start Campus:

Customize Your Portfolio: Tailor your portfolio to highlight your data analysis, visualization, and reporting skills, with a focus on projects that demonstrate your ability to collect, clean, analyze, and visualize data effectively.
Optimize Your Resume: Highlight your relevant data analysis, business intelligence, or related experience, as well as your technical skills and industry-relevant keywords.
Prepare for Technical Challenges: Brush up on your SQL, Python, or R skills, as well as your data visualization and reporting techniques, using sample datasets and practicing common data analysis exercises.
Research Start Campus: Learn about Start Campus' company culture, values, and mission, as well as the data-driven decision-making processes used within the organization. Prepare thoughtful questions to ask during the interview process to demonstrate your interest and understanding of the role.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and data analysis industry-standard assumptions. All details should be verified directly with Start Campus before making application decisions.

Data Center Tools and Reporting Specialist