Analytics Engineer

Sotalent; West of England; On-site; GBP 60,000 - 90,000; Full time

Job summary

Sotalent is seeking an Analytics Engineer to shape data products, analytics models, and experimentation frameworks for a leading global digital platform. You will build scalable data infrastructure and turn complex datasets into trusted business insights.

Join a high-impact Retail Media Insights & Enablement team, collaborating with Data Scientists, ML Engineers, Analysts, and Product teams to push analytics innovation. Experience with dbt, cloud warehouses, and BI tools is highly valued.

Qualifications

• Strong SQL skills with experience building scalable analytics data models.
• Hands-on production experience with dbt.
• Experience with cloud data warehouses such as Amazon Redshift or Google BigQuery.
• Knowledge of Airflow or similar orchestration tools.
• Understanding of data quality, testing, monitoring, and CI/CD practices.
• Experience supporting BI and visualisation platforms such as Tableau, Looker Studio, or QuickSight.
• Familiarity with Git workflows and software engineering best practices.
• Experience with Python is beneficial.

Responsibilities

• Design and maintain scalable analytics models and semantic datasets powering Retail Media reporting and experimentation
• Build modular data transformations using dbt and SQL following analytics engineering best practices
• Define and maintain core KPIs including campaign performance, ROAS, conversion metrics, and advertiser insights
• Develop and orchestrate reliable data workflows using tools such as Airflow
• Ensure high data quality through testing, monitoring, CI/CD, and Git-based workflows
• Collaborate with Data Scientists, ML Engineers, Analysts, and Product teams on experimentation and analytics initiatives
• Support dashboards, internal tools, AI-driven analytics workflows, and machine learning systems
• Contribute to documentation, shared tooling, and data engineering best practices across the wider data community

Skills

SQL

dbt

Python

Airflow

Git

CI/CD

Tools

Redshift

BigQuery

Tableau

Looker Studio

QuickSight

Job description

Join a high-impact Retail Media Insights & Enablement team helping shape the data products, analytics models, and experimentation frameworks behind a leading global digital platform. This role is ideal for an Analytics Engineer passionate about scalable data infrastructure, modern analytics engineering, and turning complex datasets into trusted business insights.

Key Responsibilities

• Design and maintain scalable analytics models and semantic datasets powering Retail Media reporting and experimentation
• Build modular data transformations using dbt and SQL following analytics engineering best practices
• Define and maintain core KPIs including campaign performance, ROAS, conversion metrics, and advertiser insights
• Develop and orchestrate reliable data workflows using tools such as Airflow
• Ensure high data quality through testing, monitoring, CI/CD, and Git-based workflows
• Collaborate with Data Scientists, ML Engineers, Analysts, and Product teams on experimentation and analytics initiatives
• Support dashboards, internal tools, AI-driven analytics workflows, and machine learning systems
• Contribute to documentation, shared tooling, and data engineering best practices across the wider data community

Requirements

• Strong SQL skills with experience building scalable analytics data models
• Hands-on production experience with dbt
• Experience with cloud data warehouses such as Amazon Redshift or Google BigQuery
• Knowledge of Airflow or similar orchestration tools
• Understanding of data quality, testing, monitoring, and CI/CD practices
• Experience supporting BI and visualisation platforms such as Tableau, Looker Studio, or QuickSight
• Familiarity with Git workflows and software engineering best practices
• Experience with Python is beneficial
• Collaborative mindset with strong problem-solving and communication skills

Nice to Have

• Experience with advertising, Retail Media, or marketing analytics datasets
• Exposure to A/B testing or experimentation platforms
• Experience working with large-scale event data or semantic layersFamiliarity with AI-assisted engineering tools such as Copilot, Cursor, Kiro, or Codex

Why Apply?

• Work on modern cloud-based analytics infrastructure at global scale
• Collaborate with multidisciplinary data and ML teams
• Strong exposure to experimentation, AI-driven analytics, and Retail Media innovation
• Opportunity to influence data standards and analytics strategy across the organisation