Analytics Engineer

Analytics Engineer

Our client, a leading global supplier for IT services, requires an experienced Analytics Engineers to be based at their client's office in London, UK.

This is a hybrid role - you can work remotely in the UK and attend the London office 3 days per week .

This is a 6+ month temporary contract to start ASAP

Day rate: Competitive Market rate

Role Description

Our client is seeking an Analytics Engineer to help advance their data-driven journey. This role offers the opportunity to work with a talented team and cutting-edge technologies such as Data Vault, Azure, AWS, Snowflake, SQL, DBT, and Airflow to deliver innovative, scalable data solutions.

You will play a key role in unlocking the potential of large data sets, enabling data-driven decision-making across the organisation. The position combines elements of data engineering, architecture, and analytics, focusing on building reliable data models and workflows for business use.

• Work with modern cloud and data technologies in a dynamic environment.
• Contribute to a major retail data transformation using Snowflake, DBT, SQL, Data Vault, and Azure/AWS.
• Collaborate with Data Architects, Data Engineers, Data Scientists, and Product Managers.
• Enjoy growth opportunities in an innovative, learning-focused culture

As an Analytics Engineer, you'll have the chance to write great SQL, design complex data models, collaborate with a talented team, and deliver robust data products alongside Data Architects, Data Scientists, Product Managers, and Data Engineers. You will bridge the gap between data engineering, data architecture and data analysis. Your focus will be on building robust and scalable data workflows to help business functions use internal data assets in an accessible and repeatable manner. This role offers a unique opportunity to combine expertise in architecture, data engineering, and data insights to drive innovation and value creation within our organisation.

Key Responsibilities:

• Bridge Between Technology and Business: Act as a liaison between engineering teams and stakeholders, translating business requirements into clear technical specifications and ensuring delivery of clean, transformed datasets
• Data Transformation & Management: Build and maintain robust data pipelines, transforming raw data into structured, analysis-ready formats
• Data Quality Assurance: Implement validation processes and governance frameworks to ensure data accuracy, consistency, and reliability
• Collaboration Across Data Teams: Partner with Data Engineers, Architects, and Analysts to design and implement integrated data solutions that meet business needs
• Data Modeling: Design, develop, and maintain scalable data models (eg, Data Vault in Snowflake) that support analytics and Business Intelligence initiatives
• Automation: Automate repetitive data workflows using Scripting and modern orchestration tools to improve scalability and efficiency
• SQL Development: Write and optimize complex SQL queries for performance, scalability, and data integrity
• Monitoring & Maintenance: Proactively monitor production data pipelines, troubleshoot issues, and ensure smooth data operations
• Design & Architecture: Contribute to system architecture, technical design, and development of high-quality data products aligned with engineering best practices
• Collaboration & Leadership: Influence and support cross-functional teams, lead outcomes, and maintain alignment with the organization's data strategy
• Insight & Impact: Apply analytical and domain knowledge to provide actionable insights, enabling data-driven decision-making and effective data storytelling
• Code Quality & Standards: Write maintainable, well-tested code following best practices and a test-driven development approach

Key Requirements:

Essential Skills:

• Proficiency in SQL for data transformation, analysis and problem-solving.
• Snowflake, DBT, Data Modelling, Data Vault, Data warehousing and GitHub
• Understanding of version control systems, continuous integration pipelines, and service-oriented architecture.
• Experience in Retail domain and Data is must.
• Understanding the need for different and appropriate design techniques, such as data vault and data warehousing
• Knowledge of Cloud technologies (AWS or Azure) and Scripting languages like Python
• Working knowledge of modern data architecture frameworks, understanding of Architecture & Engineering
• Highly numerate background with the ability to drive business change through data.
• Excellent communication skills, capable of explaining complex information in simple terms using available documentation tools.
• Strong problem-solving skills and attention to detail, with a curiosity to explore opportunities and solve problems logically.
• Delivery of solutions with longevity and maintainability following the latest Agile practices.
• Understanding of Relational (and non-relational) databases and when to use them.
• Standards/Principles and knowing when and how to implement frameworks and when to make suggestions for new Standards.
• Collaboration & Communication: Strong interpersonal skills with the ability to work cross-functionally with stakeholders, engineers, and analysts.

Desirable Skills:

• Knowledge of Data Visualization Tools: Experience with tools such as MicroStrategy/Power BI
• Terraform: Experience with Terraform and Terragrunt for infrastructure as code
• GenAI: Experience with Generative AI technologies

Due to the volume of applications received, unfortunately we cannot respond to everyone.

If you do not hear back from us within 7 days of sending your application, please assume that you have not been successful on this occasion.