Analytics Engineer

Role Overview

As an Analytics Engineer, you will own and evolve the BI team’s technical infrastructure, bridging technical data systems with the analytical needs of the business. You’ll collaborate closely with Data Engineering to deliver analytics-ready data and support BI and metric-driven decision-making.

Key Missions

• Own and evolve BI infrastructure, ensuring alignment with the broader Data Engineering architecture.
• Partner with Data Engineering to deliver clean, reliable, analytics-ready data into the BI workspace.
• Develop curated data layers to improve data quality and usability.
• Design data models for business metrics and performance KPIs.
• Work with business stakeholders to ensure data structures reflect real-world logic.

Responsibilities / Scope

• Build and maintain metric-supporting data models.
• Translate business requirements and metric definitions into scalable, robust models.
• Implement and maintain Git-based CI/CD workflows for analytics/data workflows.

Requirements

• 3–5+ years as an Analytics Engineer, Data Engineer, or similar (analytics-oriented).
• Familiarity with Fivetran ingestion tools.
• Experience with dbt and modern data modeling best practices.
• Strong communication and stakeholder management skills.
• Hands-on SQL, Python, and Spark for data processing, automation, and integrations.
• Snowflake proficiency.
• Familiarity with AWS analytics services (e.g., Redshift, Athena, S3, SageMaker).
• Git-based CI/CD workflow experience (GitLab preferred).

Nice-to-Haves

• Familiarity with data mesh and domain-oriented data products.
• Experience optimizing cross-cloud data architecture or hybrid environments.
• Knowledge of semantic layers, metrics stores, or analytics engineering frameworks.
• Experience supporting BI/analytics teams directly.