Staff Analytics Engineer: Semantic Layer & Data Standards

D8 LooP; United Kingdom; Remote; GBP 70,000 - 110,000; Full time

Job summary

D8 LooP is seeking a senior data specialist to shape the semantic layer and analytics standards for its spend-management platform. You will define data modelling approaches, govern the data contracts, and lead AI-assisted migrations across the analytics stack.

Working with backend and product teams, you will ensure scalable, cost-efficient data architectures and a single source of truth for analysts and AI agents.

Qualifications

• Proficient in Python and SQL with a focus on performance and cost in analytics.
• Deep BigQuery and SQL expertise including performance considerations and architectures for complex domains.
• Deep dbt modelling practices and a clear view of modelling architecture across functions.
• Experience with the listed tech stack: GCP, BigQuery, dbt Core, Airflow, SQL, Python, Claude Code, GitHub Copilot.
• Engage upstream with backend and product engineers to drive data contracts and schema ownership upstream.
• Design and maintain the semantic layer as the single source of truth queried by AI agents, BI tools and analysts.
• Cost and performance optimization for data warehousing and migrations using AI tooling.

Responsibilities

• Set data modelling standards for the function across all domains and levels of complexity.
• Lead migrations and warehousing efforts with AI-assisted tooling to accelerate data modelling.
• Own the semantic layer and analytics standards within the Data Services & Governance team.
• Collaborate with backend and product engineers to enforce data contracts and schema ownership upstream.

Skills

Python

SQL

Tools

GCP

BigQuery

dbt Core

Airflow

Claude Code

GitHub Copilot

Job description

D8 LooP is seeking a senior data specialist to shape the semantic layer and analytics standards for its spend-management platform. You will define data modelling approaches, govern the data contracts, and lead AI-assisted migrations across the analytics stack.

Working with backend and product teams, you will ensure scalable, cost-efficient data architectures and a single source of truth for analysts and AI agents.