Analytics Engineer

John Goddard Associates; Little London; On-site; GBP 65,000 - 75,000; Full time

Job summary

A leading logistics firm in London is seeking a Data Engineer to join their new data transformation team. You will play a crucial role in creating scalable data infrastructure and analytics solutions, utilizing Azure Databricks, SQL, and various BI tools. Ideal candidates will have strong proficiency in Python and experience with modern data stacks. This position is based on-site five days a week in central London, offering a salary between £65,000 and £75,000 based on experience.

Qualifications

• Advanced technical proficiency in SQL, Python, and modern data transformation tools.
• Experience in cloud data platforms like Azure Databricks or Snowflake.
• Strong software engineering practices including version control and CI/CD.

Responsibilities

• Collaborate with Data Engineer to design and maintain scalable data pipelines.
• Create and maintain dimensional data models for business intelligence.
• Implement automated data quality checks and monitoring systems.

Skills

SQL

Python

dbt

Azure Databricks

Data modelling

Power BI

Git

CI/CD

Tools

Azure Data Factory

Snowflake

Tableau

Looker

Job description

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 the Data Science, Engineers, Analytics and Analyst professionals, you will have the opportunity 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.
• DCreate 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, Snowflake, or similar).
• 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.

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