Senior Data Modeling & Visualization Engineer

Lengow; Barcelona; On-site; EUR 70,000 - 95,000; Full time

Job summary

Lengow is seeking a Senior Engineer — Data Modeling & Visualization to strengthen its semantic modeling, metrics, and dashboard capabilities. You will transform vast catalog and product data into reliable models and clear KPIs for internal and customer-facing data products.

You will own the data layer, collaborate with product and business stakeholders, and ensure reusable data assets rather than ad hoc reports, all within a senior analytics engineering context.

Qualifications

• Proven ability to design analytical models and semantic layers.
• Experience building dashboards for internal and customer-facing use.
• Strong SQL skills and familiarity with modern BI tools.
• Ability to challenge unclear metrics and define KPIs.

Responsibilities

• Own semantic and visualization layer of internal and customer data products.
• Define KPIs, dimensions, facts, grains, filters, and business rules.
• Design reusable analytical models for dashboards and data products.
• Build and improve dashboards in Looker Studio with clarity and performance.
• Translate requirements into modeled datasets, dashboards, and validation rules.
• Write advanced SQL transformations and contribute to dbt workflows.
• Collaborate with Senior Data Engineers on data quality and reliability.
• Ensure reusable data assets replace ad hoc reporting.

Skills

Data modeling

Data visualization

Analytics engineering

Data quality

Stakeholder communication

SQL

Tools

SQL

BigQuery

Google Cloud Platform

dbt

Airflow

Cube.js

Looker Studio

Power BI

MariaDB

PostgreSQL

Talend

Apache NiFi

Job description

Lengow is seeking a Senior Engineer — Data Modeling & Visualization to strengthen its semantic modeling, metrics, and dashboard capabilities. You will transform vast catalog and product data into reliable models and clear KPIs for internal and customer-facing data products.

You will own the data layer, collaborate with product and business stakeholders, and ensure reusable data assets rather than ad hoc reports, all within a senior analytics engineering context.