Data Engineer

Tekst; Oost-Vlaanderen; Hybrid; EUR 70,000 - 95,000; Full time

Benefits offered by this job

Equity

Competitive salary

Job summary

Tekst is seeking a data engineer to build and own the data platform from scratch in Belgium. You will unify data from product databases, events, HubSpot and finance systems to enable trusted, self-serve metrics across Product, GTM and Finance.

You’ll define core metrics and ROI, and drive data quality, security and accessibility. You’ll shape the architecture of warehouses or lakehouses, choose tooling with CTO guidance, and empower teams to answer questions quickly while maintaining GDPR

Qualifications

• Medior-senior experience in data engineering.
• Strong SQL and Python; hands-on with a modern warehouse/lakehouse.
• Familiar with dbt, Airflow; tooling-agnostic.
• Experience defining metrics used across teams.
• Great communication and ability to influence stakeholders.

Responsibilities

• Zero-to-one build: design and create the data platform.
• Build pipelines from product DB, event stream, HubSpot and finance systems.
• Own core metrics including usage, ROI and customer value.
• Enable teams with self-serve access to metrics.
• Run a simple intake process for data/research questions.

Skills

SQL

Python

Data architecture

Cross-functional metrics

Enablement mindset

Communication & influence

Tools

Snowflake

Databricks

BigQuery

dbt

Airflow

Job description

About Tekst & Our Mission

At Tekst, we believe in a world where enterprise processes run themselves, and people get to do the work they love. Our mission is to make enterprise processes self‑improving. To get there, we’re building the context layer that lets AI agents work at scale on the back‑office processes that actually matter. With enterprise customers like Daikin, Colruyt, Mitsubishi and Nokia and $13.5M in Series A funding, we cut through the AI hype to deliver real, measurable automation.

The Role

As our first dedicated Data Engineer, you’ll build our data infrastructure from zero to one and then own it. Product usage, GTM and finance/contract data all live in separate systems today. You’ll bring them together, so Solutions can show a customer their ROI with contract and usage data side by side, and Product, GTM and Finance can work from shared definitions of what \"active\" or \"value delivered\" means.

Our product generates real volume and variety of data, which makes this a genuine data engineering challenge: you’ll own the architecture end to end — which warehouse or lakehouse (Snowflake, Databricks, or whatever you believe is right — tooling choices are yours to make, in consultation with our CTO), how ingestion and transformation are structured, and how people across the company find and trust the data once it’s there.

Once the foundation is live, your focus expands to enabling others: giving Product, GTM and Finance self‑serve access to the metrics they need. You’ll also run the intake for data/research questions that need real analysis.

What will you be doing?

• Zero-to-one build: Design and build our data platform from scratch, warehouse/lakehouse, ingestion and transformation




• Pipelines that matter: Build and maintain pipelines from the product database, event stream, HubSpot, and finance/contract systems, bringing usage, GTM and contract data into one place.




• Own the metrics, including value and ROI: Define and own our core metrics; product usage as well as the customer value and ROI numbers Solutions needs to prove impact to enterprise accounts, so Product, Sales, CS and Finance work from the same numbers.




• Enable teams to self‑serve: Build the access and tooling that let Product, GTM and CS answer their own questions directly.




• Run the research funnel: Set up a simple intake process for data/research questions from across the company and personally pick up the ones that need real analysis.




• Bring people along: Win buy-in from stakeholders across data, product and engineering for shared definitions and self‑serve tools, so the platform actually gets used.




• Keep it trustworthy: Testing, monitoring, GDPR compliance and cost control as the platform matures from build to maintenance.

What's in it for you?

• Competitive salary and equity.




• Real, rare ownership: you decide the architecture and tooling for a data platform built from nothing.




• Your work directly feeds the ROI story Solutions tells enterprise customers like Daikin, Nokia and Colruyt.




• Fun team-buildings, social and sports activities.




• Being surrounded by an all-star team with a unicorn dream and a strong on office culture.

Job requirements

What we're looking for

• Experience: Medior-senior experience in data engineering




• Tech stack: Strong SQL and Python; hands‑on with a modern warehouse or lakehouse (Snowflake, Databricks, BigQuery, or similar) and transformation/orchestration tooling (dbt, Airflow, or similar). We’re tooling‑agnostic — bring your own opinion.




• Data architecture: You think in terms of where data lives, how it flows, and how to make it discoverable and trustworthy for people who aren’t data engineers.




• Cross‑functional metrics: Experience defining metrics that multiple teams (product, sales, finance) genuinely align on and adopt — this is as much about alignment as it is about SQL.




• Enablement mindset: You get energy from building systems that let other teams move fast on their own.




• Communication & influence: You can win stakeholders across teams over to shared definitions and tools — success here depends on alignment as much as on technical execution.




• Bonus: Experience with BI tooling (Looker, Metabase, Power BI) and using AI tools to speed up analysis.




• Fluent in written and spoken English; Dutch is a plus.