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For Companies At a Glance
- Tasks: Design scalable data models and build robust transformation workflows for impactful data products.
- Company: Join a high-performing data function in a dynamic London tech environment.
- Benefits: Competitive day rate, hybrid work model, and opportunities for professional growth.
- Why this job: Bridge technical delivery with business insight and drive real impact through data.
- Qualifications: Strong SQL skills, experience with Snowflake, and a knack for data modelling.
- Other info: Collaborative culture with a focus on innovation and career advancement.
The predicted salary is between 43200 - 72000 £ per year.
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
- Strong understanding of data modelling techniques including Data Vault
- Experience using GitHub and version control systems
- Understanding of CI/CD pipelines and service-oriented architecture
- Knowledge of cloud platforms (AWS and/or Azure)
- Proficiency in Python (primary), SQL and Bash
- Experience with modern data architecture frameworks
- Strong understanding of relational and non-relational databases
- Excellent communication skills, able to explain complex concepts clearly
- Strong analytical mindset with the ability to drive business impact through data
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
Analytics Consultant in City of London employer: Stott and May
Contact Detail:
Stott and May Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Consultant in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your SQL and data modelling skills. We recommend doing mock interviews with friends or using online platforms to get comfortable with articulating your experience.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your best work with data pipelines and models. This gives potential employers a tangible sense of your capabilities and how you can contribute to their team.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Analytics Consultant in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Analytics Engineer role. Highlight your SQL expertise, experience with data modelling, and any relevant projects that showcase your skills. We want to see how you can bridge the gap between technical delivery and business insight!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data and how your experience aligns with our needs. Don’t forget to mention your familiarity with tools like Snowflake and DBT, as well as your understanding of CI/CD pipelines.
Showcase Your Projects: If you've worked on any relevant projects, make sure to include them in your application. Whether it's building data pipelines or automating processes, we love seeing real-world examples of your work. It helps us understand your hands-on experience!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we’re excited to see what you bring to the table!
How to prepare for a job interview at Stott and May
✨Know Your SQL Inside Out
As an Analytics Engineer, strong SQL skills are a must. Brush up on your SQL queries and be ready to demonstrate your ability to transform and model data. Prepare examples of how you've used SQL in past projects to solve real business problems.
✨Understand the Tech Stack
Familiarise yourself with the tools and technologies mentioned in the job description, like Snowflake, DBT, and Azure. Be prepared to discuss how you've used these tools in your previous roles and how they can benefit the company’s data architecture.
✨Showcase Your Problem-Solving Skills
Be ready to tackle hypothetical scenarios during the interview. Think about how you would approach transforming raw data into analysis-ready datasets or automating repetitive processes. This will show your analytical mindset and ability to drive business impact through data.
✨Communicate Clearly
Excellent communication skills are essential for this role. Practice explaining complex technical concepts in simple terms. You might need to bridge the gap between engineering teams and stakeholders, so being able to articulate your thoughts clearly will set you apart.
