Since 2009, Lengow has been the indispensable e-commerce platform for multi‑channel expansion in the European market: marketplaces, price comparison websites, affiliate marketing, display ad retargeting, social media, etc.

Our Data team

Join a dynamic Tech, Data & Product team of 50 professionals with diverse expertise. You’ll report to the Head of Data and work closely with our Tech, Product, and business teams.

The Data Team is a key driver of innovation at Lengow. From enabling access to insights for employees to creating custom data products for clients, our mission is to transform raw data into business impact. We’re expanding our scope and shaping the future of data at Lengow.

What the Data team does

Empower business decisions with relevant insights and accessible data tools

Guide product development through data‑driven features, metrics, and insights

Manage and optimize custom data products for clients

Enhance our data stack and tools for scalability, reliability, and performance

Cultivate a data‑first culture by translating business needs into actionable insights

Your mission

We are seeking a Senior Analytics Engineer — Data Modeling & Visualization to strengthen the Data Team’s semantic modeling, metrics, and dashboarding capabilities.

With access to vast data — thousands of catalogs, millions of products, and billions of entries scraped from e‑commerce websites — you’ll help transform complex data into reliable models, clear metrics, and useful dashboards for internal and customer‑facing data products.

This role owns the Data Team’s semantic and visualization layer: business‑facing data models, metric definitions, dashboards, validation rules, and documentation. You will work closely with the Product Manager, who owns Product‑side framing, prioritization, stakeholder alignment, and business acceptance. Your role is to translate Product and business needs into reliable models, clear KPIs, useful dashboards, and maintainable data products.

This is a senior technical role at the intersection of analytics engineering, data modeling, and data visualization. It is not a Product Manager role or a pure Data Engineering role. It is also not focused on ad hoc reporting: requests should be turned into reusable, maintainable data assets whenever they create recurring value.

Your key responsibilities:

Own the semantic and visualization layer of Lengow’s internal and customer‑facing data products

Define and document KPIs, dimensions, facts, grains, filters, assumptions,



and business rules

Design reusable analytical models and semantic layers across dashboards and data products

Build and improve dashboards in Looker Studio that are clear, useful, performant, and decision‑oriented

Transform Product and business requirements into modeled datasets, dashboard specifications, validation rules, and documentation

Write advanced SQL transformations and contribute to dbt workflows

Collaborate with Senior Data Engineers on upstream data quality, data contracts, performance, reliability, and maintainability

Challenge unclear metric definitions, incomplete acceptance criteria, misleading visualizations, and one‑off requests that should become reusable data products

Communicate assumptions, limitations, edge cases, feasibility, risks, and trade‑offs clearly to technical and non‑technical stakeholders

Recruitment Process

Pre‑interview: Chat with Alexandre, Head of People (30')

Team interview: Meet Sebastien (VP Data) and team members (60')

Final interview: Present a technical case to Sebastien and Olivier (Chief Product and Technology Officer) (60')

Requirements We’re looking for a senior data professional who combines technical rigor, strong data modeling skills, visualization expertise, and business understanding.

You should be able to understand a business question, challenge vague definitions, design the right analytical model, and deliver a dashboard or data product that can be trusted over time.

Here’s what you bring to the table:

Experience: 5+ years in analytics engineering, data visualization engineering, BI engineering, data engineering, or a similar data role

Data modeling: strong understanding of facts, dimensions, grains, aggregations, metric definitions, semantic consistency, and business rules

Data visualization: proven ability to design dashboards that are not only visually clear, but useful for real decisions

Engineering fluency: advanced SQL, strong analytical rigor, and good understanding of data quality, lineage, testing, and transformation workflows

Collaboration: ability to work with Product, business stakeholders,



and Senior Data Engineers without becoming a substitute Product Manager or a support desk

Mindset: autonomous, structured, constructive, and able to push back when definitions, requirements, or implementation choices are unclear or unsafe

Tools & tech: experience with SQL, BigQuery, Google Cloud Platform, dbt, Airflow, Cube.js, Looker Studio, Power BI, MariaDB, and PostgreSQL. Familiarity with ETL/ELT tools such as Talend or Apache NiFi is a plus in our current context

We value your ideas and welcome recommendations on tools, modeling practices, visualization standards, and data product quality.

Bonus points if you:

Know and are passionate about web, e‑commerce, marketplaces, retail, SaaS, or product analytics

Have worked on customer‑facing dashboards or data products

Have experience with semantic layers, metrics layers, or governed KPI frameworks

Have experience with data contracts or data quality frameworks

Have strong UX instincts for data products and dashboards

What success looks like Success will be evaluated through the quality, reliability, adoption, and maintainability of internal and customer‑facing data products.

Examples of successful outcomes include:

Critical KPIs have clear definitions, grains, assumptions, and validation rules

Dashboards are trusted, documented, actively used, and decision‑oriented

Dashboard logic is implemented in reusable modeled datasets instead of duplicated across reports

Stakeholders understand metric behavior, limitations, and edge cases

Product/Data collaboration with the Product Manager is structured and repeatable

BI assets meet agreed standards for readability, performance, maintainability, and business usefulness

Technical environment Our environment includes SQL, BigQuery, Google Cloud Platform, Cube.js, dbt, Airflow, Looker Studio, Power BI, MariaDB, PostgreSQL, Talend, Apache NiFi, and internal and customer‑facing analytics use cases.

Benefits

Ticket restaurant 8 euros by day

Malakoff Humanis Private insurance & Prevoyance

3 Remote days per week

Adaptable hours

Bike mileage allowances or 50% of transportation tickets

Remote allowances

Professional events (Devoxx, Meetup ...) and regular internal cohesion

Weekly Happy Break on Thursday Evening at the office with food and beverage

Syntec forfait jours with RTT - 218 annual working days, ie minimum 9 days off on top of 5 weeks legal paid leave

Choose your laptop OS. You can work on MacOS, Windows or Linux

#J-18808-Ljbffr

📌 Senior Data Engineer (Madrid)
🏢 Lengow
📍 Madrid