Analytics Engineer

This range is provided by McGregor Boyall. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

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Consultant – Infrastructure, Cloud & DevOps at McGregor Boyall

London (five days per week on site)

£65-75k (dependent on experience)

The Highlights

This global logistics business, based in central London, is undergoing an exciting data transformation programme as it invests in a new team charged with building and implementing a new Azure Databricks platform. Working five days a week in the central London office, you\’ll join this growing team and play a key role in building and deploying robust data infrastructure and analytics solutions using modern data stack.

The business is evolving and maturing its approach to data, creating an opportunity to build data solutions that have a significant impact on the performance of the business. Working closely with a multi‑skilled team of Data Science, Engineers, Analytics and Analyst professionals, you will have the opportunity to build your skills in analytics engineering, responding to business and project needs rather than operating as a narrow silo.

You’ll work hands‑on with Azure Databricks, Azure Data Factory, Delta Lake, and Power BI to create scalable data models, automated pipelines, and self‑service analytics capabilities. This is a fantastic opportunity to join a newly created team, work on new development projects and contribute to the implementation of a new data strategy.

The Position

Key responsibilities and primary deliverables:

• Collaborate with Data Engineer in the design, build, and maintain scalable data pipelines using Azure Data Factory and Databricks to automate data ingestion, transformation, and processing workflows.
• Create and maintain dimensional data models and semantic layers that support business intelligence and analytics use cases.
• Build and optimise data transformation workflows using dbt, SQL, and Python to create clean, well‑documented, and version‑controlled analytics code.
• Implement automated data quality checks, monitoring systems, and alerting mechanisms to ensure data reliability and trustworthiness across the analytics platform, linking issues to the business impact.
• Develop reusable data assets, documentation, and tools that enable business users to independently access and analyse data through Power BI and other visualization platforms.
• Work closely with data analysts, and business stakeholders to understand requirements and translate them into technical solutions.
• Create and maintain technical documentation, establish coding standards, and maintain data catalogue to support governance and compliance requirements.

Skills & Experience

• Advanced technical proficiency in SQL, Python, and modern data transformation tools (dbt strongly preferred), with experience in cloud data platforms (Azure Databricks).
• Proven experience designing and implementing scalable data architectures, including dimensional modelling, data lakehouse/warehouse concepts, and modern data stack technologies.
• Strong software engineering practices including version control (Git), CI/CD pipelines, code testing, and infrastructure as code principles.
• Deep understanding of data quality frameworks, data governance principles, and experience implementing automated monitoring and alerting systems.
• Analytics platform expertise with hands‑on experience in business intelligence tools (Power BI, Tableau, Looker) and understanding of self‑service analytics principles.
• Strong problem‑solving abilities with experience troubleshooting complex data issues, optimizing performance, and implementing scalable solutions.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Information Technology

Industry

Information Services

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

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