Senior Analytics Engineer - Data Modeling & Visualization

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, , 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, , dbt, Airflow, Looker Studio, Power BI, MariaDB, PostgreSQL, Talend, Apache NiFi, and internal and customer-facing analytics use cases.

Benefits

Joining Lengow is also an opportunity to benefit from many advantages :

• Ticket restaurant 8 euros by day
• Malakoff Humanis Private insurance & Prevoyance.
• 3 Remote days per week
• Flexible 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.