Club Data Analyst

Basic Fit International B.V.; Hoofddorp; Hybrid; EUR 39,000 - 61,000; Full time

Benefits offered by this job

Travel allowance

Bike plan

Health insurance discounts

Remote work allowance

Pension plan

Gym access

Job summary

Basic-Fit is hiring a Club Data Analyst to turn facility and financial data into actionable insights for club operations. You will work with Databricks and SQL to create dashboards and identify cost drivers.

You will collaborate with facility managers, flag issues, and contribute to long-term data landscape projects; hybrid work with 4 days in the office and 1 day from home, offering growth opportunities.

Qualifications

• Bachelor's/Master's degree (HBO/WO) in Data Science, (Business) Informatics, or similar.
• Strong SQL skills and experience with Databricks/Genie or a comparable data platform.
• Experience building and maintaining dashboards and a solid grasp of statistical analysis.
• Knowledge of and experience with data related to buildings and Facility Management (e.g. maintenance, ticketing, asset, or supplier/SLA data).
• Affinity with cost and financial analysis (cost-per-intervention, benchmarking).
• Experience independently building your own views/aggregations on existing data.

Responsibilities

• Analyse existing facility ticket, maintenance, and financial data (mainly in Databricks) to identify recurring issues, root causes, and cost drivers.
• Build and maintain dashboards, so managers have a standing, self-serve overview instead of one-off analyses.
• Flag day-to-day issues and anomalies for the responsible managers to investigate and act on.
• Evaluate the cost impact of processes and supplier performance (SLA adherence, benchmarking between suppliers, cost-per-intervention on recurring assets).
• Write your own SQL/Genie queries and build new views and aggregations on existing data.
• Projects: your scope naturally grows as the long-term data-landscape approach makes more club data available.

Skills

SQL

Databricks

Genie

Dashboards

Cost analysis

Education

Bachelor's/Master's in Data Science or related

Tools

Databricks

Genie

Job description

This Is What Your Role Looks Like

Are you excited about turning building and facility data into insights that make a real difference to how our clubs run? Are you able to spot a recurring issue in a mountain of maintenance data and translate it into a number a manager can act on? Our Facility Team is expanding, and we're looking for a Club Data Analyst who will help our Facility Department make the most out of data and take club performance to the next level. You'll turn raw club data — starting with facility ticket data (preventive and corrective maintenance) and financial data — into standing dashboards, flagged issues, and cost/impact figures.

Your Responsibilities

• Analyse existing facility ticket, maintenance, and financial data (mainly in Databricks) to identify recurring issues, root causes, and cost drivers.
• Build and maintain dashboards, so managers have a standing, self-serve overview instead of one-off analyses.
• Flag day-to-day issues and anomalies for the responsible managers to investigate and act on.
• Evaluate the cost impact of processes and supplier performance (SLA adherence, benchmarking between suppliers, cost-per-intervention on recurring assets).
• Write your own SQL/Genie queries and build new views and aggregations on existing data.
• Projects: your scope naturally grows as the long-term data-landscape approach makes more club data available.

Who Are You?

You're an analytical thinker who can digest complex maintenance and cost data, spot trends versus noise, and translate them into a clear signal for non-technical stakeholders such as facility managers. You're a self-starter and proactive in flagging issues, without pulling the decision or the fix toward yourself.

Additionally, we're looking for someone who has:

• A completed Bachelor's/Master's degree (HBO/WO), in Data Science, (Business) Informatics, or similar.
• Strong SQL skills and experience with Databricks/Genie or a comparable data platform.
• Experience building and maintaining dashboards and a solid grasp of statistical analysis.
• Knowledge of and experience with data related to buildings and Facility Management (e.g. maintenance, ticketing, asset, or supplier/SLA data) — a requirement for this role.
• Affinity with cost and financial analysis (cost-per-intervention, benchmarking).
• Experience independently building your own views/aggregations on existing data.

What We Offer You At Basic-Fit, it's not just about work, it's about your growth.

As a Club Data Analyst, you'll have the freedom to make an impact and develop yourself in a dynamic environment.

What you can expect from us:

• Learning & Development: Unlimited access to GoodHabitz and LinkedIn Learning.
• Career Growth: Plenty of opportunities for professional and personal development.
• Work Culture: An informal, international, and down-to-earth environment. We value working together, so we work 4 days in the office, 1 day from home.
• Innovation: Your ideas contribute to strategic projects.
• Salary: A monthly gross salary between €3.500 and €5.500 based on 40 hours, depending on your experience and background.
• Perks & Benefits:
  • Travel allowance
  • bike plan
  • health insurance discounts
  • remote work allowance
  • pension plan (52% contribution by Basic-Fit)
• Fitness: Access to our gym at HQ.

About Basic-Fit

Basic-Fit is Europe's leader in the value-for-money fitness market, with more than 4.7 million members across 1,650+ clubs in 6 countries. We are continuously growing and improving. If you're looking for a place where you can make an impact while having fun at work, you've come to the right place!

What Makes Us Unique?

• Work with Impact: What you do makes a difference.
• We don't just work for our members, partners, and teams—we work with them.
• Collaboration: Everyone works together to achieve goals and celebrate success.
• Diversity & Inclusion: We welcome everyone into our workplace.

Questions? Feel free to contact Yara van Bodegom at [e-mail].