Analytics Engineer

Role Overview

The Data Enablement Team is responsible for building and maintaining the foundational data infrastructure that powers decision-making across the company. We focus on the ingestion, transformation, and modeling of data. Our goal is to ensure that our data is clean, reliable, and accessible through our centralized data warehouse.

What You Will Do

In this role, you will bridge the gap between data engineering and data analysis by transforming raw data into clean, well-modeled datasets that power business decisions. You’ll work primarily with Snowflake, dbt, and Python to build scalable data models and maintain a robust analytics infrastructure.

Why It Might Be a Fit

You will be expected to work with stakeholders, gather requirements, and deliver reliable, timely data solutions that meet business needs.

Requirements

• Bachelor’s degree in Computer Science, Data Science, or related field
• Proven experience in a technical analytics role
• Very good knowledge of SQL and proven experience with Python
• Hands-on experience with dbt for data modeling and transformation.
• Proficiency with Snowflake or a similar cloud data warehouse platform
• Experience with reporting and dashboard tools (Power BI, Tableau, Apache Superset)
• Ability to work both independently and in a team-oriented environment
• Experience working with large and messy datasets
• You enjoy collaborating with other engineers and analysts
• Proven ability to manage stakeholders independently, translate business requirements into technical solutions, and communicate findings clearly.
• You will always be thinking about new ways you can better solve problems using data
• You have great communication skills both written and verbal.
• You embrace the YouGov values

Benefits

• Best-in-class benefits to support their physical, financial, and emotional wellbeing
• Sense of belonging and uniqueness in a supportive workplace
• Equal Opportunity Employer
• Data Privacy

Tagged as: Data Analysis, Power BI, Python, Snowflake, SQL