The engineers involved at MAXQ Analytics are compensated for their time and effort based on their seniority.

<aside> Key people and communication:

Compensation Owner: Philip Boontje
Finance & Administration Manager: Casimir Laurentius
Slack channel: #gen-billing, #gen-sales
Email: [email protected] </aside>

Earl Nightingale (1921-1989) – "Make yourself indispensable, and the money will take care of itself"

Revenue Share

We apply an 80/20 rule when sharing the revenue between the company and the engineer. The 80% goes to the engineer and the 20% goes to the company to compensate for account management, software licences, administration, legal advice, lead generation, business development, partner development, product development, financial liabilities and reputation risk.

For Junior Engineers this 80% revenue share is earned in their 5th year. They start off with 60% in their first year, which grows with +5% annual increments. We apply this logic to compensate the more senior engineers for their time when they share their experience.

Example calculation

In the example below, we describe a 2nd year junior data engineer that joins our company and grows into the role of senior data engineer:

Year	Role	Hourly Rate	Comments	Rev-share	Compensation
2025	Junior Data Engineer	80 EUR	1 year experience	65%	48 EUR
2026	Junior Data Engineer	85 EUR		70%	55 EUR
2027	Junior Data Engineer	85 EUR		75%	60 EUR
2028	Medior Data Engineer	130 EUR	Promotion to Medior	80%	98 EUR
2029	Medior Data Engineer	135 EUR		80%	108 EUR
2030	Medior Data Engineer	140 EUR		80%	112 EUR
2031	Medior Data Engineer	145 EUR		80%	116 EUR
2032	Senior Data Engineer	225 EUR	Promotion to Senior	80%	180 EUR

Seniority

Junior Engineer

When people are starting with minimal experience we are looking for the following traits:

Creative and innovative – Able to think outside the box and come up with novel solutions to technical challenges. Enjoys experimenting with new technologies and approaches to improve data processes and workflows.
Independent & self-starting – Capable of taking initiative and driving tasks forward with minimal supervision. Comfortable working in a fast-paced environment where problem-solving and adaptability are key.
Humble and keen to learn – Open to feedback and eager to grow both personally and professionally. Willing to ask questions, seek guidance, and continuously develop skills in data engineering and related technologies.
Systematic thinker – Approaches problems methodically and can break down complex data challenges into manageable components. Strives for efficiency and consistency in data pipelines, architecture, and workflows.
Making complexity simple – Able to transform intricate technical concepts into clear, understandable insights for both technical and non-technical audiences. Strives to build scalable and maintainable solutions that simplify data processes.
Proficient in English – Capable of communicating effectively in English, both written and verbal, to collaborate with international teams, document work, and present findings clearly.