> Markdown version of [/jobs/ext/3443711-data-engineer-spanish-speaker](https://www.wearedevelopers.com/jobs/ext/3443711-data-engineer-spanish-speaker). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer - Spanish speaker

- **Company:** Amaris
- **Location:** Cerdanyola del Vallès, Spain
- **Contract:** Permanent contract
- **Skills:** Microsoft Azure, BigQuery, Customer Data Management, Information Engineering, Data Mining, Data Structures, Python (Programming Language), Query Optimization, Power BI, SQL Databases, Data Processing, Snowflake, Powerquery, Data Analytics, Optimizely, Databricks
- **Published:** September 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a6faf29e6bdc816e

## About the Role

* 3-5 years of experience in Data Analytics, Data Engineering or similar roles, preferably in Ecommerce / Retail environments.

 * Strong experience with SQL, including query optimisation and working with complex data structures.

 * Advanced knowledge of Power BI, including DAX and Power Query, with experience building dashboards from scratch.

 * Hands-on experience with Databricks - mandatory.

 * Experience with BigQuery and Snowflake.

 * Experience with Python

 * Experience with tools such as GrowthBook, Optimizely or Azure DevOps would be a plus.

 * Fluent Spanish and good command of English.

## Description

* Analyse Ecommerce and customer data to generate actionable business insights and support strategic decision-making.

 * Develop and optimise SQL queries, working with data distributed across multiple tables and sources.

 * Work with BigQuery and Snowflake, ensuring efficient data extraction, transformation and analysis.

 * Build Power BI dashboards from scratch, including data modelling, DAX and Power Query.

 * Define and monitor Ecommerce KPIs, supporting business and stakeholder reporting.

 * Work with Databricks to analyse and process data across different sources.

 * Integrate digital, CRM, transactional and other business data to support analytical use cases.

 * Monitor data quality and communicate insights and recommendations to business stakeholders.