Analytics Engineer

Role: Analytics Engineer
Location: London, England (5 days on site)
Type: Permanent
Reporting to: Head of Data

Company

Stanton House has partnered with a leading global organisation in the maritime sector to recruit an experienced Analytics Engineer for their London-based team.

About the Role

Our client is undergoing a major data transformation and is seeking a skilled Analytics Engineer to help shape and deliver modern data solutions. This role sits at the intersection of data engineering and analytics, enabling data-driven decision-making across the business.

You will work closely with the Head of Data to design and implement scalable data infrastructure, automated pipelines, and self-service analytics capabilities using cutting-edge technologies such as Azure Databricks, Azure Data Factory, dbt, SQL, Python, and Power BI.

Key Responsibilities

• Data Infrastructure & Pipelines: Build and maintain automated data ingestion and transformation workflows using Azure Data Factory and Databricks.
• Data Modelling: Develop and manage dimensional models and semantic layers to support analytics and BI use cases.
• Analytics Development: Create clean, well-documented transformation workflows using dbt, SQL, and Python.
• Data Quality: Implement automated checks and monitoring systems to ensure data accuracy and reliability.
• Self-Service Enablement: Deliver reusable data assets and documentation to empower business users through Power BI and other visualization tools.
• Collaboration: Partner with analysts and stakeholders to translate business requirements into technical solutions.
• Governance & Standards: Maintain technical documentation, coding standards, and data catalogues for compliance.
• Mentorship: Share best practices and provide guidance to junior team members.

Skills & Experience

• 5+ years in data engineering or analytics engineering roles.
• Advanced proficiency in SQL, Python, and modern transformation tools (dbt preferred).
• Experience with cloud data platforms (Azure Databricks, Snowflake, or similar).
• Strong understanding of data architecture, dimensional modelling, and modern data stack concepts.
• Familiarity with version control (Git), CI/CD, and infrastructure-as-code principles.
• Expertise in BI tools (Power BI, Tableau, Looker) and self-service analytics.
• Excellent problem-solving and communication skills.
• Agile working experience and ability to manage multiple priorities.
• A continuous learning mindset and enthusiasm for emerging technologies.