Analytics Consultant
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Analytics Engineer
Location: London - Hybrid (minimum 2 days per week in the office)
Contract Duration: 6 months
Day Rate: Market rate (Inside IR35)
Overview
We are seeking an experienced Analytics Engineer to join a high-performing data function in London. This role sits at the intersection of data engineering, data architecture and analytics, bridging technical delivery with business insight.
You will design scalable data models, build robust transformation workflows and deliver high-quality data products in collaboration with Data Architects, Data Scientists, Product Managers and Data Engineers. The focus is on enabling business teams to use internal data assets in a structured, accessible and repeatable manner.
As an Analytics Engineer, you will write high-quality SQL, design complex data models and build reliable data workflows. You will translate business requirements into scalable technical solutions and contribute to the organisation’s broader technical strategy.
Key Responsibilities
- Act as a bridge between engineering teams and stakeholders, translating business needs into technical specifications
- Transform and structure raw data into reliable, analysis-ready datasets
- Build and maintain scalable data pipelines and workflows
- Develop and maintain complex data models representing business processes and entities
- Implement data validation and quality assurance processes
- Collaborate with data engineers and architects to ensure seamless integration across platforms
- Automate repetitive data processes to improve efficiency and scalability
- Contribute to the design and delivery of data products aligned to engineering principles and roadmaps
- Support architectural decisions and technical design discussions
- Deliver clear, high-quality insights and support data storytelling initiatives
- Write maintainable, testable code aligned with coding standards and Agile practices
Essential Skills & Experience
- Strong SQL expertise for transformation, modelling and analysis
- Experience with Snowflake, DBT and modern data warehousing approaches
Technical Environment
Languages: Python, SQL, Bash
Cloud: Azure, AWS
Data & Platforms: Snowflake, Delta Lake, Redis, Azure Data Lake
Tools: Airflow, DBT, Docker
Infrastructure & Operations: Terraform, GitHub Actions, Azure DevOps, Azure Monitor
Desirable Skills
- Experience with data platforms such as Snowflake or Azure Data Lake
- Experience deploying models as APIs (e.g. FastAPI, Azure Functions)
- Knowledge of monitoring, model performance tracking and observability practices
- Familiarity with orchestration tools such as Airflow or Azure Data Factory