AI-First Analytics Engineer — Hybrid (Fabric, Power BI)

Crew Clothing Company; Kingston upon Thames; Hybrid; GBP 60,000 - 85,000; Full time

Job summary

Crew Clothing Company seeks an Analytics Engineer to join its Data & Analytics team in Kingston upon Thames. You will turn a Fabric Lakehouse and Power BI semantic model into live data products for trading, buying, retail, and finance teams.

This AI-first role uses Claude Code and MCP tooling to build data lakes, dashboards and documentation, while applying DevOps practices and ensuring data quality across multiple brands.

Qualifications

• 3+ years in analytics engineering, BI development or data engineering.
• Strong SQL skills with complex views, CTEs and window functions.
• Hands-on Power BI experience including DAX and semantic model design.
• Python for data manipulation (Pandas/PySpark) and automation.
• Familiarity with basic DevOps practices and version control.
• Experience with Microsoft Fabric or Databricks and cloud data platforms.
• Interest in AI-assisted development and retail analytics applications.

Responsibilities

• Own delivery against the D&A roadmap and data product priorities.
• Build, maintain and document Fabric Lakehouse data transformations.
• Extend Power BI semantic model with new data sources and brands.
• Leverage Claude Code and MCP tooling in daily analytics work.
• Apply Git-based deployment pipelines and environment governance.
• Own Fabric data pipelines and data quality checks.
• Design dashboards for leadership and trading teams to drive decisions.
• Lead onboarding of new brand data onto the Fabric platform.

Skills

SQL

Power BI

Python

Pandas

PySpark

AI tooling

Tools

Microsoft Fabric

Databricks

Git

Claude Code

MCP tooling

Job description

Crew Clothing Company seeks an Analytics Engineer to join its Data & Analytics team in Kingston upon Thames. You will turn a Fabric Lakehouse and Power BI semantic model into live data products for trading, buying, retail, and finance teams.

This AI-first role uses Claude Code and MCP tooling to build data lakes, dashboards and documentation, while applying DevOps practices and ensuring data quality across multiple brands.