Overview In this Analytics Engineer role, you will shape how ALOHAS measures performance, from defining metrics to delivering trusted dashboards and AI-ready data. You'll work at the center of our data stack with BigQuery, dbt, and Lightdash, partnering with a Data Engineer and cross-functional teams. You own end-to-end questions, ensuring metrics are well-defined, documented, and accessible.

This is a hands-on, builder role at a growing fashion-focused company committed to sustainable practices.

Compensaciones / Beneficios Culture of Freedom, Responsibility & Trust

Flexible Working Hours

Hybrid Work Model

Summer Hours

Mental Health Support

Team wellbeing initiatives and disconnect days

Responsabilidades Build trusted data models in dbt (facts, dimensions, curated marts) used by multiple teams

Translate business questions into clean models across sales, retail, supply chain, marketing, inventory, and customer behavior

Write tests, documentation, and exposures to ensure data trust

Adhere to dbt conventions to maintain scalable, consistent data architecture

Own canonical metric definitions across the business and maintain semantic layer in Lightdash

Collaborate with stakeholders to align metrics with presente operations

Design and own Lightdash explorations and dashboards for self-serve governance

Ensure metrics/models are canonical sources of truth for downstream AI agents and dashboards

Contribute to the team by sharing knowledge, reviewing work,



and helping others

Requisitos principales Hands-on SQL + dbt experience with modular models, tests, docs, and macros

Strong understanding of business/financial metrics across commercial, unit economics, marketing, retention, and operations

Experience with a modern data warehouse (BigQuery preferred; Snowflake/Redshift/Databricks acceptable) and cost/performance-aware querying

Data quality discipline including freshness, tests beyond not_null, anomaly detection, and documentation

Experience with AI-ready workflows and Claude/OpenAI/Cursor-like tools for SQL, debugging, and documentation

PR-based workflow familiarity (Git, code reviews, dbt CI) and collaboration with a Data Engineer

Experience with BI/semantic tools (Lightdash, Looker, dbt Semantic Layer, Cube) is a plus

Familiarity with e-commerce/ERP sources (Shopify, Odoo) is a plus

Experience modeling DTC data complexity (multi-currency, multi-warehouse, returns, multi-channel) is a plus

Python for scripting or analyses is a plus

Background in fast-paced DTC/e-commerce/fashion is a plus

Degree in quantitative/technical field or equivalent practical experience

Fluent in Spanish and English

Three years with strong ownership (not strictly counted)

Strong cross-functional communication

Analytical curiosity

Ownership mindset

SQL dbt core + dbt Cloud for CI/CD

BigQuery or other modern data warehouses

📌 Implementation Engineer (Software) (Barcelona)
🏢 ALOHAS
📍 Barcelona