AI-Enabled Data Analytics Engineer

Principle; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

33 days annual leave including bankhol

Job summary

Principle is hiring an AI-Enabled Data Analytics Engineer in Greater London to design scalable data and AI-assisted automation solutions that improve business decision-making.

This hands-on role emphasizes Databricks, SQL and Python, with practical use of Claude Code, Cursor, GitHub Copilot or ChatGPT to accelerate development and ensure reliable AI outputs.

Qualifications

• 3+ years' experience across Analytics Engineering, Data Engineering or Data Analytics.
• Strong hands-on Databricks.
• Advanced SQL.
• Strong Python.
• Experience with ETL/ELT, data modelling and data pipelines.
• Practical experience using AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot or ChatGPT.
• Exposure to AI agents, prompt engineering or context engineering.
• Strong understanding of data quality and governance.
• Ability to independently review and validate AI-generated outputs.
• Strong stakeholder communication and problem-solving skills.
• 33 days annual paid leave including bank holidays.

Responsibilities

• Design, build and optimise data pipelines and analytics solutions using Databricks.
• Develop SQL, Python and PySpark solutions for transformation, analytics and automation.
• Build and improve AI agents, reusable workflows, prompt templates and automation solutions.
• Use AI development tools for coding, debugging, testing, documentation and code review.
• Apply prompt engineering and context engineering to improve the reliability of AI-generated outputs.
• Validate AI-generated code, analysis and recommendations before production/business use.
• Build and maintain documentation, context files, knowledge sources and business rules governing AI behaviour.
• Partner with stakeholders to translate business requirements into scalable data and AI solutions.
• Maintain strong standards around data quality, governance and performance.

Skills

Databricks

SQL

Python

PySpark

AI development tools

Claude Code

Cursor

GitHub Copilot

ChatGPT

Data pipelines

ETL/ELT

Data governance

Tools

Claude Code

Cursor

GitHub Copilot

ChatGPT

Job description

We are hiring an AI-Enabled Data Analytics Engineer to join a global technology organisation, building scalable data, analytics and AI-assisted automation solutions that improve business decision-making.

This is a hands-on engineering role for someone strong in Databricks, SQL and Python who is already using tools such as Claude Code, Cursor, GitHub Copilot or ChatGPT to accelerate development.

You won't just use AI-generated outputs- you'll be expected to validate, challenge and improve them, ensuring solutions are technically accurate, reliable and relevant to the business.

What you'll be doing

• Design, build and optimise data pipelines and analytics solutions using Databricks
• Develop SQL, Python and PySpark solutions for transformation, analytics and automation
• Build and improve AI agents, reusable workflows, prompt templates and automation solutions
• Use AI development tools for coding, debugging, testing, documentation and code review
• Apply prompt engineering and context engineering to improve the reliability of AI-generated outputs
• Validate AI-generated code, analysis and recommendations before production/business use
• Build and maintain documentation, context files, knowledge sources and business rules governing AI behaviour
• Partner with stakeholders to translate business requirements into scalable data and AI solutions
• Maintain strong standards around data quality, governance and performance

What we're looking for

• 3+ years' experience across Analytics Engineering, Data Engineering or Data Analytics
• Strong hands-on Databricks
• Advanced SQL
• Strong Python
• Experience with ETL/ELT, data modelling and data pipelines
• Practical experience using AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot or ChatGPT
• Exposure to AI agents, prompt engineering or context engineering
• Strong understanding of data quality and governance
• Ability to independently review and validate AI-generated outputs
• Strong stakeholder communication and problem-solving skills.
• 33 days annual paid leave including bank holidays