Analytics Engineer - Build Trusted Data & AI Insights

Glovo Group; Barcelona; On-site; EUR 40,000 - 65,000; Full time

Job summary

Glovo is seeking an Analytics Engineer to join the Marketplace Experience Data team in Barcelona. You will build solid SQL foundations, document data models, and produce validated outputs to empower business decisions over the next 12–18 months.

You will collaborate with Business stakeholders and other Data teams, translate requirements into practical data solutions, and grow into owning small data products end-to-end while adopting AI tools responsibly and ensuring data quality.

Qualifications

• 1–2 years in Analytics Engineering or related data roles.
• Strong SQL foundations; ability to write and optimise analytical queries.
• Solid understanding of data modelling fundamentals (joins, granularity, fact/dimensions).
• Practical experience using AI tools (ChatGPT, Copilot, Gemini) and validating outputs.
• Fluent English; able to explain technical topics to diverse stakeholders.

Responsibilities

• Develop reliable datasets, data models and analytical assets for business and technical teams.
• Translate business requirements into simple, well-defined data solutions with senior Analytics Engineers.
• Write, test and maintain SQL transformations with focus on quality, readability and documentation.
• Validate data outputs for accuracy, understandability and fit for purpose.
• Collaborate with stakeholders to turn pain points into better data products; grow to own small data products end-to-end.

Skills

SQL foundations

Data modelling

AI tools usage

Query optimisation

Analytical thinking

Fluent English

Tools

BigQuery

dbt

Looker

Git

Job description

Glovo is seeking an Analytics Engineer to join the Marketplace Experience Data team in Barcelona. You will build solid SQL foundations, document data models, and produce validated outputs to empower business decisions over the next 12–18 months.

You will collaborate with Business stakeholders and other Data teams, translate requirements into practical data solutions, and grow into owning small data products end-to-end while adopting AI tools responsibly and ensuring data quality.