We are looking for an Agile, product-oriented Senior Analytics Engineer to drive our modern data architecture. You will be the bridge between raw data and business value for our digital products and online services. In this role, speed and value are key. You will adopt an MVP (Minimum Viable Product) mindset to launch data products quickly, iterate fast, and provide actionable insights for our Marketing and Finance teams. You will work on our cutting-edge stack—building robust pipelines in dbt and BigQuery, and exposing data through our next-generation semantic
layer in Omni Analytics.

What you will do
● Modern Data Modeling: Design, build, and maintain scalable dbt models in BigQuery. Transform raw data into clean, tested, and documented data marts ready for analysis.
● MVP Delivery: Adopt a fast-paced, product-oriented mindset. Launch Minimum Viable Products for data reporting to give product and business stakeholders quick answers, then iterate based on feedback.
● Semantic Layer Ownership: Implement and govern the business logic in Omni Analytics (or similar modern BI tools),



ensuring metrics are defined once and trusted by everyone.
● Cross-Functional Analytics: Collaborate closely with Marketing and Finance departments to understand our digital platform metrics (CAC, LTV, ROI, conversion funnels, retention, and MAUs) and translate them into technical solutions.
● Quality & CI/CD: Apply software engineering best practices to data: version control (Git), automated testing, and CI/CD workflows for data pipelines.

Requirements
● Experience: 6+ years in a Data Engineering, Analytics Engineering, or advanced BI role.
● Modern Data Stack (Essential): Extensive experience with dbt and cloud data warehouses (preferably BigQuery, though Snowflake/Redshift is valid).
● BI & Semantic Layers: Experience with Omni Analytics is highly desired. Alternatively, strong experience in Looker (LookML), Power BI, or Tableau, with a clear understanding of semantic layers and govern

📌 Senior Analytics Engineer (Chile)
🏢 10Pearls
📍 Chile