ph3Overview /h3 pThis critical role sits at the intersection of Data Engineering and Data Analytics, focusing on transforming raw data into high‑quality, trustworthy, and easily consumable datasets and visualisations for business users. The adecuado candidate will possess a strong background in SQL, dbt, data modelling, ETL/ELT principles and experience with modern cloud data platforms. /p h3Core Responsibilities /h3 ul liDevelop and maintain transformation best practices in ELT pipelines: Design, develop, and maintain efficient and scalable workflows using tools like dbt to transform raw data loaded into our data warehouse (Snowflake) into clean, ready‑to‑use data models. /li liData modelling: Implement best‑practice data modelling and software engineering techniques to ensure data structures are optimised for performance, accuracy, and ease of use in reporting and analytical applications (e.g., CI/CD, testing, lineage). /li liData quality and testing: Write comprehensive data quality checks, tests, and monitoring scripts to ensure the accuracy, completeness, and reliability of all transformed data assets. Establish and maintain documentation for all data transformations and models. /li liCollaboration: Work closely with Data Analysts and business users to understand their reporting needs and optimise data models to support their analytical use cases. Collaborate with Data Engineers on data ingestion strategies and platform optimisation. /li liPerformance optimisation: Tune and optimise SQL queries and data models to reduce latency and improve the performance of our data warehouse and downstream applications. /li liTool adoption:



Champion the adoption of modern data stack tools and practices (e.g., Git, CI/CD). /li liBuild scalable, compelling data visualisations in Looker that can be used by large teams. /li /ul h3Required Qualifications /h3 ul liExperience: 3+ years of experience in a data‑focused role (e.g., Analytics Engineer, Data Analyst, BI Developer). /li liSQL Mastery: Expert‑level proficiency in writing and optimising complex SQL queries. /li liData Transformation Tooling: Hands‑on experience with dbt (Data Build Tool) or similar data transformation frameworks is essential. /li liData Warehousing: Experience working with cloud‑based data warehouses such as Snowflake, Google BigQuery, or Amazon Redshift. /li liData modelling: Solid understanding of data warehousing concepts, ETL/ELT principles, and dimensional modelling techniques. /li liVersion Control: Proficiency with Git for collaborative development and version control. /li liFamiliarity with reporting/BI tools like Looker. /li /ul h3Preferred Qualifications /h3 ul liPython expertise for automation, integration, and orchestration. /li liExperience with semantic layers. /li liExperience with orchestration tools like Airflow. /li liKnowledge of modern software engineering practices applied to data (e.g., modularity, code review, testing). /li /ul pThis role requires you to be based within commuting distance of our London or Barcelona hub. For certain roles, we can help with relocation from anywhere in the world. /p pWe’re an equal opportunity employer, which means you’re welcome at Perk regardless of how you look, where you’re from, or anything else that makes you, well, you. /p /p #J-18808-Ljbffr

📌 Analytics Engineer (Barcelona)
🏢 Perk
📍 Barcelona