Analytics Engineer

CompanyStanton House

LocationLondon Area, United Kingdom

Posted At1/9/2026

UK Visa Sponsorship Analytics

Analytics are greyed out due to low classification confidence (40.0%).

Occupation Type

Telecoms and related network installers and repairers

Occupation Code Skill LevelMedium Skilled

Sponsorship Salary Threshold

£41,700 (£21.38 per hour)

Standard minimum applies

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Description

Role: Analytics Engineer

Location: London, England (5 days on site)

Type: Permanent

Salary: Competitive

Reporting to: Head of Data

Company

Stanton House has partnered with a leading global organisation 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.