Analytics Engineer

Role Overview

At XR, Analytics Engineers are the bridge between data engineering and data analysis. They transform raw data into trusted, analytics-ready datasets that empower analysts, data scientists, and business stakeholders to focus on insights and strategy. Think of Analytics Engineers as owning the user experience (UX) of data—ensuring it’s well-organized, reliable, and easy to use.

This is a high-visibility role where you’ll partner closely with leaders across Finance, Product, and Operations to ensure they have timely, accurate, and trusted data to drive critical decisions. You’ll also play a central role in XR’s hub-and-spoke BI model: maintaining centralized governance and standards, while enabling distributed analysts across the business to explore and self-serve with confidence.

Key Responsibilities

· Data Transformation & Modeling: Build analytics-ready datasets using a layered approach (Medallion Architecture – Bronze, Silver, Gold) in Databricks.

· Delta Live Tables (DLT): Design, manage, and optimize DLT pipelines to deliver reliable and automated transformations at scale.

· Enable Self-Service: Deliver curated, governed datasets in BI tools (Looker, Omni.co, etc.) to empower analysts and business stakeholders.

· Data Quality Monitoring: Implement validation and monitoring processes to ensure accuracy, consistency, and trust in data across all layers.

· Governance & Documentation: Define and maintain data naming conventions, dictionaries, and semantic models for standardization.

· Access & Security: Establish and enforce dataset access controls that balance governance with usability.

· Cross-Functional Collaboration: Work closely with Finance, Product, and Operations leaders as well as analysts, data scientists, and engineers to enrich semantic models and accelerate time-to-insights.

· Advanced SQL skills and expertise in data modeling (star schema, dimensional modeling, semantic layers).

· Hands-on experience with Databricks, including Delta Live Tables (DLT).

· Experience building datasets with a layered architecture (Medallion: Bronze, Silver, Gold).

· Familiarity with ETL/ELT tools (dbt, Fivetran, Airflow, or similar).

· Experience with BI platforms (Looker, Power BI, Tableau, or Omni.co. Looker and Omni a plus).

· Understanding of data governance and self-service enablement.

· Strong communication and collaboration skills, especially when working with non-technical business leaders.

· Proficiency with Git and modern data stack practices.