> Markdown version of [/jobs/ext/3598207-data-engineer](https://www.wearedevelopers.com/jobs/ext/3598207-data-engineer). 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 - **Company:** Amaris - **Location:** Barcelona, 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:** October 7, 2026 - **Apply:** https://es.trabajo.org/oferta-3453-e4484cdba01a079454b49bdc7c7fd967 ## 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 Would you like to start a new professional adventure as a Data Engineer in one of our opportunities in the Retail & Ecommerce industry in Cerdanyola del Valles? Your missions? 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.