The Opportunity

A leading global professional services organisation is seeking an experienced Analytics/ Prompt Engineer to join a high-performing Data & AI transformation team.

This role sits at the intersection of data engineering and analytics - transforming raw, ingested data into trusted, structured, analytics-ready data products that power business intelligence, reporting, and advanced analytics initiatives across the enterprise.

You will play a key role in building semantic layers, defining KPIs, and ensuring data quality and governance across a modern cloud data platform.

Key Responsibilities

Design and implement scalable data models within Databricks.
Transform raw datasets into curated, analytics-ready data products using Delta Lake and Spark.
Build and maintain semantic layers for business reporting.
Translate stakeholder requirements into technical specifications.
Define KPIs and controlled vocabulary across data products.
Own reconciliation logic and ensure data consistency across teams.
Optimise SQL queries and workflows for performance.
Collaborate closely with Data Engineers, Analysts and Data Scientists.
Maintain documentation and governance standards.
Support CI/CD processes and version control workflows.

Required Experience

Strong SQL expertise (data modelling & optimisation).
Hands-on Databricks experience (Delta Lake + Spark).
Experience with dbt or similar transformation frameworks.
Python for data manipulation and automation.
Azure cloud experience.
Familiarity with BI tools (Power BI preferred).
Strong understanding of data warehousing concepts.
Exposure to Git-based version control & CI/CD pipelines.
Ability to engage confidently with business stakeholders.

Nice to Have

Exposure to ML/AI workflows within Databricks.
Experience building semantic layers from scratch.
Enterprise-scale governance experience.

Ideal Profile

This role suits someone who:

Thinks in terms of data products, not just pipelines.
Enjoys bridging technical delivery with business impact.
Can operate in a fast-paced, collaborative environment.
Takes ownership of data quality and KPI consistency.

Why Apply?

Modern cloud stack (Databricks + Azure).
Strategic transformation programme.
Enterprise-scale data challenges.
High stakeholder visibility.
Strong likelihood of contract extension.

If you would like to explore further, please apply or get in touch directly for a confidential discussion.

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.

McGregor Boyall

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