Analytics Engineer

Analytics Engineer

Maidstone Full-Time 28800 - 48000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Transform and model marketing data for decision-making and campaign activation.
  • Company: Wyoming Interactive is an award-winning digital consultancy for global leaders in various sectors.
  • Benefits: Enjoy hybrid work, performance bonuses, profit sharing, and 28 days holiday plus extra time off.
  • Why this job: Join a supportive team shaping digital performance for top brands while developing your skills.
  • Qualifications: 3+ years in data roles, strong SQL and Snowflake skills, and experience with marketing tools.
  • Other info: Flexible working options and opportunities for professional development and networking.

The predicted salary is between 28800 - 48000 £ per year.

Wyoming Interactive is an award-winning digital consultancy that designs and delivers sophisticated digital platforms for global leaders in Life Sciences, Financial Services, and Technology. Our work helps enterprise clients better understand, engage, and convert their customers, with the right data powering the right decisions.

We’re now hiring an Analytics Engineer to support a high-profile international client. This role focuses on transforming and modelling marketing data so it can be used for decision-making, personalisation, and campaign activation across multiple platforms and markets.

As an Analytics Engineer, you’ll sit between data engineering and marketing activation. Your job is to make raw data usable, building scalable, governed datasets that power segmentation, performance measurement, and automated marketing journeys. You won’t be running campaigns or designing the customer journey, but you’ll ensure that data flows cleanly and accurately across the Martech stack so CRM teams can.

Day to day you’ll be designing and maintaining high-quality, analysis-ready datasets that support CRM, product, and marketing teams in making informed decisions. Using Snowflake alongside tools like dbt and SQL, you’ll model data to enable segmentation, performance tracking, and personalised marketing. You will have the opportunity to work across a broad Martech stack, including platforms such as HubSpot, Shopify, Google Analytics, and Meta ads, ensuring that clean, consistent data is available where and when it is needed.

You’ll build and manage governed data pipelines using tools like RudderStack and Azure Data Factory, and support reporting and visualisation through platforms such as Looker Studio and PowerBI, collaborating with internal stakeholders and client teams to ensure data models align with business priorities, while maintaining strong standards around privacy, compliance, and governance.

What You’ll Bring

  • 3+ years working in data, analytics, or martech-adjacent engineering roles
  • Strong skills in SQL, Snowflake, and data transformation/modelling tools (e.g. dbt)
  • Experience integrating data from Google Analytics and HubSpot
  • Familiarity with CDPs or event tracking platforms such as RudderStack
  • Ability to work closely with marketing, analytics, and technical teams, translating business goals into technical solutions
  • A thoughtful, detail-oriented approach to data quality, documentation, and governance

Nice to Have

  • Experience supporting CRM or marketing teams at enterprise scale
  • Previous work in ecommerce, consumer products, or lifestyle sectors
  • Familiarity with CI/CD principles or modern data ops workflows
  • Understanding of campaign enablement use cases (e.g. personalisation, journey orchestration, audience targeting)

Why Join Wyoming Interactive?

  • We offer the best of both worlds, a tight-knit consultancy environment backed by large-scale client impact.
  • You’ll work with smart, supportive teammates who value your input, while building platforms that shape the digital performance of leading global brands.
  • Hybrid, remote, and flexible working options
  • Performance-based bonus
  • Annual profit share
  • 28 days holiday + extra time off at Christmas & New Year
  • Skills development opportunities and regular conference access
  • Edinburgh HQ with social events and team gatherings

Curious to Learn More? Send us your CV or get in touch for an informal chat, we’re always happy to walk through the opportunity and answer your questions.

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Contact Detail:

Wyoming Interactive Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Analytics Engineer

✨Tip Number 1

Familiarise yourself with the specific tools mentioned in the job description, such as Snowflake, dbt, and SQL. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.

✨Tip Number 2

Network with professionals in the analytics and marketing fields, especially those who have experience with Martech stacks. Engaging in conversations about data integration and transformation can provide insights and potentially lead to referrals.

✨Tip Number 3

Prepare to discuss how you've previously ensured data quality and governance in your past roles. Be ready to share specific examples of how your attention to detail has positively impacted data-driven decision-making.

✨Tip Number 4

Research Wyoming Interactive and their clients to understand their business priorities and challenges. Tailoring your discussions around how your skills can directly address their needs will demonstrate your genuine interest in the role.

We think you need these skills to ace Analytics Engineer

SQL
Snowflake
Data Transformation
Data Modelling (e.g. dbt)
Data Integration
Google Analytics
HubSpot
RudderStack
Azure Data Factory
Looker Studio
PowerBI
Data Governance
Attention to Detail
Collaboration Skills
Problem-Solving Skills
Understanding of Marketing Technologies
CI/CD Principles
Data Quality Assurance

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data, analytics, and martech engineering roles. Emphasise your skills in SQL, Snowflake, and any data transformation tools you've used, as these are crucial for the Analytics Engineer position.

Craft a Compelling Cover Letter: Write a cover letter that connects your background to the specific requirements of the role. Mention your experience with integrating data from platforms like Google Analytics and HubSpot, and how you can contribute to the company's goals.

Showcase Your Technical Skills: In your application, provide examples of projects where you've built governed data pipelines or worked with tools like dbt and RudderStack. This will demonstrate your hands-on experience and understanding of the technical aspects of the role.

Highlight Collaboration Experience: Since the role involves working closely with marketing and analytics teams, include examples of how you've successfully collaborated with cross-functional teams in the past. This will show your ability to translate business goals into technical solutions.

How to prepare for a job interview at Wyoming Interactive

✨Know Your Tools

Familiarise yourself with the specific tools mentioned in the job description, such as SQL, Snowflake, and dbt. Be prepared to discuss your experience with these technologies and how you've used them to transform and model data in previous roles.

✨Understand the Martech Stack

Research the various platforms listed, like HubSpot, Google Analytics, and RudderStack. Show that you understand how these tools interact and how clean data flows through them to support marketing efforts. This will demonstrate your ability to bridge the gap between data engineering and marketing activation.

✨Highlight Data Quality and Governance

Emphasise your attention to detail and your approach to data quality, documentation, and governance. Prepare examples of how you've ensured data accuracy and compliance in past projects, as this is crucial for the role.

✨Prepare for Technical Questions

Expect technical questions related to data transformation and modelling. Brush up on your knowledge of data pipelines and be ready to explain your thought process when designing analysis-ready datasets. This will showcase your analytical skills and problem-solving abilities.

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