Data Engineer

🌍 Why this role exists

Sortlist is an AI-powered marketplace connecting companies with top service providers in marketing, web & IT. We help thousands of businesses find the right partners faster.

At Sortlist, data should align people around decisions — not trigger debates about metrics.

We’re entering a new chapter for data. We’re moving from dashboard-centric analytics to a model-driven foundation where metrics are consistent, trusted, and scalable across teams. This evolution is key to unlocking real self-service analytics and, increasingly, AI-assisted workflows like text-to-SQL.

We’re hiring someone excited by this transition — someone who wants to help define what modern BI looks like in a growing scale-up.

You’ll join a small, experienced data team and work closely with Product, Finance, Growth, and Engineering to make data trusted, shared, and genuinely useful.

🔍 What you’ll do

• Design and evolve analytical data models that remain stable as the product and business evolve
• Challenge vague or poorly framed questions and turn them into clear, well-defined metrics
• Make the “right number” easy to find, understand, and trust — especially for:
• Financial performance
• Investment and prioritisation decisions
• Product focus and trade-offs
• Build and document data models that scale beyond you, enabling reliable self-service and AI-assisted analytics
• Play a key role in modernising our analytics tooling:
• Contribute to the transition toward more modern data consumption patterns
• Help ensure AI-assisted workflows can safely rely on strong, well-defined data models
• Participate in selecting, configuring, and improving the tools used by end users

Dashboards may exist.

Models and decisions are not optional.

⚙️ How you’ll work

• You focus on durability and rigour: models are testable, documented, and resilient to change
• You adapt your approach to how decisions are actually made — not how you wish they were made
• You communicate clearly with both technical and non-technical stakeholders
• You treat stakeholders as partners: you co-design metrics, you don’t just “take requirements”

Strong opinions about data quality and modeling are not just welcome — they’re expected.

🚀 Why This Role Will Stretch You

You don't need to have led a data transformation before. What matters is your ability to think critically about trade-offs, communicate across teams, and improve your judgment over time.

This role will stretch your ability to:

• Think in systems — seeing how data decisions ripple across Product, Finance, and Growth
• Balance rigour with pragmatism — knowing when perfect is the enemy of good
• Influence without authority — building trust and co-designing metrics with stakeholders
• Shape tooling strategy — contributing to what modern BI looks like, not just using it

If you're mid-level, you'll learn how to design durable data models and navigate ambiguous business problems. If you're senior, you'll sharpen your ability to drive consensus and make strategic trade-offs.

🔧 Current data stack & direction

Today, our core stack includes:

• Warehouse: BigQuery
• Modeling layer: dbt
• BI / internal tools: Tableau, Retool

This stack is intentionally evolving.

We are actively transitioning toward more modern, model-driven analytics tooling, with a strong focus on:

• Reusable, well-defined data models
• Scalable self-service analytics
• AI-assisted data exploration built on solid foundations

You will be a key contributor in shaping this transition — both technically and conceptually.

👤 Who we’re looking for

This role is open to mid-level profiles and senior candidates, under freelance or employee contracts.

You’ll thrive here if you:

• Are comfortable with ambiguity and incomplete problems
• Enjoy connecting data to real business and financial outcomes
• Are proactive and don’t wait for perfect instructions
• Care more about adoption and impact than ownership or control
• Like working with many different people and perspectives

Must-haves:

• Strong data modeling and durable analytics systems
• Turns vague questions into trusted metrics
• Communicates insights clearly to all stakeholders
• Drives adoption across teams
• Fluent in English and French (our working languages)

Nice-to-haves:

• Business acumen, links metrics to outcomes
• Solid foundations in data systems and pipelines
• Experience with AI-assisted analytics or modern BI stacks (dbt, Snowflake, Looker)

⛔ Please do not apply if

• You mainly want to build dashboards or reports
• You prefer waiting for detailed specs before acting
• You don’t have strong opinions about data modeling, rigor, and long-term quality

💰 Compensation

• Freelance Contract: €80,000 – €90,000 yearly rate.
• Employee Contract: €43,000 – €57,600 gross, plus a €600 mobility budget or company car, meal vouchers, comprehensive health insurance, training budget: €1,000/year, net allowances and more.
• We care more about mindset, judgment, and fit than about rigid seniority labels

📍 Location & setup

• Belgium-based role (near Wavre preferred)
• Hybrid setup: remote work encouraged up to 2–3 days per week

❤️ Why You'll Love Working Here

Sortlist is a scale-up where teams truly matter. You'll join a small data team (Senior Data Engineer + Head of Data). We provide: MacBook Pro, €1,000 training budget, health insurance, hybrid work (2-3 days remote).

You’ll work with people who are:

• Strong at what they do
• Pragmatic and opinionated
• Genuinely kind and enjoyable to collaborate with

This role sits at the intersection of many teams. Success here depends as much on human qualities and trust-building as on technical skill.

If you’re excited about building something meaningful, with people you actually enjoy working with, we’d love to hear from you.

The Bottom Line

In this role, you'll help define what modern, model-driven analytics looks like in a growing scale-up. You'll move from building dashboards to building systems that enable reliable self-service and AI-assisted decision-making.

If you care about building data foundations that matter — not just dashboards that get forgotten — and you want to work with people you actually like, apply now and help us shape the future of analytics!