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- Tasks: Deliver insights from data to inform marketing strategies and decisions.
- Company: Join a fast-growing travel business with exciting opportunities.
- Benefits: Competitive salary, flexible working, and career growth potential.
- Other info: Dynamic role with the chance to work across various teams.
- Why this job: Be a key player in shaping marketing strategies through data-driven insights.
- Qualifications: Expertise in SQL and Python, with a passion for data analysis.
The predicted salary is between 45000 - 55000 £ per year.
As a Marketing Data Engineer, you’ll be responsible for delivering reporting and insight to inform strategy and commercial decision making. Taking information from multiple sources including Advertising Platforms and Data Warehouses to provide insight that helps elevate the understanding of customers, potential customers, advertising, commercial ROI and website.
Building reporting that tells a story, creating visualised reporting that drives actionable insights. This role is a newly created position in a fast-growing travel business, providing great scope to grow within the business. It requires a naturally curious, inquisitive mindset, someone who loves to delve into the data, solve problems, stitch things together and help the teams gain greater insight into the customer and commercial detail.
You’ll be data hungry, love learning and finding workarounds and fixing gaps – a role where you can add great value and be involved across the business:
- Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines to ingest data from diverse sources including booking engines and digital marketing platforms like Google Ads or Meta Ads. Develop a plan for leveraging customer data in the absence of CRM & CDP systems.
- Marketing Analytics Support: Develop data models to support advanced marketing use cases such as Marketing Mix Modelling (MMM), multi-touch attribution, and customer lifetime value (CLV) predictions.
- Data Quality & Governance: Ensure all data handling complies with UK GDPR and PECR, specifically managing PII (Personally Identifiable Information) and marketing consent across all villa-related datasets.
- Stakeholder Collaboration: Translate complex technical data structures into clear insights for non-technical marketing managers to help them understand campaign performance and villa occupancy trends.
- Infrastructure Management: Manage and optimise cloud-based data warehouses or lakes, typically using Microsoft Azure, AWS, or Google Cloud Platform (GCP).
- Technical Proficiency: Expert-level SQL and Python are essential for data transformation and automation.
- Tooling Experience: Familiarity with modern data stack tools such as dbt for transformations, Airflow for orchestration, and Terraform for infrastructure-as-code.
Data Engineer (Marketing) employer: Gail Kenny Executive Recruitment
Contact Detail:
Gail Kenny Executive Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Marketing)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those that highlight your ability to build ETL pipelines or develop marketing analytics models. This will give you an edge when chatting with hiring managers.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Be ready to discuss how you've used these tools in real-world scenarios, especially in relation to marketing data and insights. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Engineer (Marketing)
Some tips for your application 🫡
Show Your Curiosity: We want to see that inquisitive mindset in your application! Share examples of how you've delved into data, solved problems, or found creative workarounds. This will help us understand your passion for data and how you can add value to our team.
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with ETL/ELT pipelines and marketing analytics. We love seeing how your skills align with the role, so don’t hold back on showcasing your technical proficiency in SQL and Python!
Keep It Clear and Concise: When writing your application, clarity is key! Use straightforward language to explain your experiences and achievements. Remember, we’re looking for someone who can translate complex data into insights, so show us you can do that right from the start.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it shows us you’re keen to join our fast-growing travel business!
How to prepare for a job interview at Gail Kenny Executive Recruitment
✨Know Your Data Tools
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss how you've used these tools in past projects, especially in relation to ETL/ELT pipelines and data transformation.
✨Understand Marketing Analytics
Familiarise yourself with concepts like Marketing Mix Modelling and customer lifetime value predictions. Being able to explain these terms and how they apply to real-world scenarios will show your potential employer that you're not just data-savvy but also understand the marketing side of things.
✨Prepare for Stakeholder Communication
Think about how you would explain complex data insights to non-technical team members. Practice simplifying technical jargon into clear, actionable insights. This will demonstrate your ability to collaborate effectively across teams.
✨Show Your Curiosity
During the interview, share examples of how you've tackled data challenges in the past. Highlight your inquisitive mindset and problem-solving skills, as this role requires someone who loves to delve into data and find solutions.