Analytics Engineer

Description

We are looking for an **Analytics Engineer** with strong technical rigor, an automation mindset, and the willingness to work in an environment where AI is not a buzzword—it’s part of daily operations. This role bridges data engineering and analytical consumption: transforming, modeling, and governing data within the data warehouse, and delivering it reliably and clearly to the visualization layer. It requires deep technical proficiency in SQL and data modeling, combined with solid hands-on experience in Power BI—the primary tool used to deliver insights to clients. The role involves direct client interaction, and leveraging AI and agents as key accelerators for speed and quality is central to the way of working. **Responsibilities** * Model and maintain data transformations in BigQuery using dbt, including version control and documentation * Write complex, optimized SQL queries—ensuring performance and clarity in the data layer that powers reports * Build, maintain, and evolve Power BI dashboards, ensuring quality, consistency, and alignment with client needs * Design and maintain the logical and semantic data layer, guaranteeing that a metric means the same thing across all consumption points * Operate the data quality and reconciliation layer, with proactive alerts that detect and classify discrepancies between sources before they reach the client * Apply efficiency best practices—including incremental models—to optimize cost and performance in the warehouse * Interact directly with clients to gather requirements, validate deliveries, and resolve technical requests—communicating clearly and confidently **Requirements** * Advanced SQL proficiency, with ability to write and optimize complex queries * Solid Power BI experience—including dashboard development and maintenance, data modeling (DAX), and data source configuration * Experience in analytical data modeling (dimensional modeling, transformation layers, consistent and reusable models) * Practical experience using dbt as the central tool for transformation, versioning, and documentation * Experience with logical and semantic data layers * Strong communication skills and experience in direct client interaction—with the ability to translate business needs into technical solutions and confidently sustain technical discussions **Nice-to-have** * Experience with BigQuery in a multi-client environment * Familiarity with pipeline orchestration tools (e.g., Airflow or equivalent) * Curiosity and hands-on experimentation with AI tools and agents **Profile** * Automation mindset: when faced with repetitive tasks, seeks to eliminate—not manually scale—them * Rigor around data consistency, reliability, and clarity in delivered outputs * Professional demeanor and strong interpersonal skills in client-facing interactions