Analytics Engineer

Overview

Analytics Engineer – Up to £75k – London 3 days a week

About the company

Join a fast-growing, global tech unicorn that is redefining the way people connect and work in real life. This company is on a mission to simplify complex processes and empower teams with data-driven insights. With a collaborative, in-person-first culture, you’ll be part of a forward-thinking organisation that values creativity, autonomy, and innovation.

The role

We are looking for an Analytics Engineer to turn raw data into clean, reliable, and actionable datasets and visualisations for business users. You will sit at the intersection of Data Engineering and Data Analytics, helping to build scalable, high-quality data pipelines and models that support decision-making across the business.

What you’ll do

• Design, build, and maintain scalable ELT pipelines using tools like dbt to transform raw data into structured, analysis-ready models.
• Implement robust data modelling and software engineering best practices to ensure accuracy, performance, and usability.
• Develop data quality tests, monitoring, and documentation to maintain trust in business data.
• Collaborate with analysts, engineers, and business stakeholders to optimise data structures for reporting and analytical workflows.
• Optimise queries and models to improve performance of the data warehouse and downstream applications.
• Build compelling data visualisations to empower teams across the organisation.
• Advocate for modern data stack tools and engineering best practices, including version control and CI/CD.

What we’re looking for

• 3+ years in a data-focused role such as Analytics Engineer, Data Analyst, or BI Developer.
• Expert-level SQL skills and experience writing complex queries.
• Hands-on experience with dbt or similar transformation frameworks.
• Experience with cloud data warehouses like Snowflake, BigQuery, or Redshift.
• Strong understanding of ETL/ELT principles, dimensional modelling, and data warehousing concepts.
• Familiarity with BI tools such as Looker and version control systems like Git.

Nice-to-haves

• Python experience for automation and orchestration.
• Knowledge of semantic layers and orchestration tools such as Airflow.
• Familiarity with modern software engineering practices applied to data, including testing, modularity, and code review.