Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and optimise data pipelines, integrate marketing tools, and develop AI solutions.
- Company: Join a Google Partner known for innovative data solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make an impact in digital marketing with cutting-edge technology and data-driven strategies.
- Qualifications: Experience in data engineering, Python, SQL, and Google Cloud Platform required.
- Other info: Collaborative environment with mentorship opportunities and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
About the Company
Our client, a Google Partner, is looking to hire an experienced Data Engineer.
About the Role
You will be part of a team responsible for the development and overall delivery of big data platform solutions, automation solutions, and data AI Agents. You will be designing and proposing effective combinations of Google Marketing Platform tools (GA4, Campaign Manager 360, Search Ads 360, etc.) and Google Cloud solutions (BigQuery, BQ Sharing (Analytics Hub), Cloud Storage, APIs, Compute Engine, etc.) to address specific client needs. You will be designing, maintaining, and optimising data infrastructure for data collection, management, transformation, and access. You will work collaboratively with internal teams and clients to uncover their unique marketing challenges, business objectives, and current architectures. You will translate their needs into actionable product roadmaps that leverage Google Marketing Platform and Google Cloud solutions.
Responsibilities
- Lead the design, development, and optimization of scalable data pipelines using Python and GCP.
- Configure and manage complex integrations between Google Marketing Platform tools, Google Cloud Projects, and other marketing systems.
- Ensure data accessibility, privacy, and security by implementing client data policies and managing data access controls.
- Build and implement custom scripts or tools using APIs and data connectors to meet specific client needs.
- Create automation and data AI agents for marketing analytics and user workflow solutions.
- Diagnose and resolve technical problems related to Google Cloud Platform setup, data flow, and reporting.
- Integrate with various marketing APIs, including Twitter/X, DV360, Google Ads, and Facebook, to extract and transform data for analysis.
- Develop and maintain data tools for paid media platforms and e-commerce, such as product feed management and bid optimization based on real-time data.
- Apply advanced data modelling techniques to identify key data aspects and categorise information effectively (e.g., customer names as strings, income/purchase as metrics, premium customer as a category).
- Collaborate with stakeholders to identify user pain points through quantitative and qualitative data, formulate hypotheses, and recommend actions to improve customer experience and web performance.
- Create comprehensive reports on data availability and enhance the presentation of availability information to customers.
- Utilize machine learning libraries for attribution and propensity modelling.
- Mentor junior data engineers and contribute to the overall data strategy.
Qualifications
- Extensive experience as a Data Engineer, with a strong background in data analysis and data science in digital marketing.
- Experience with creating AI Agents.
- Develop and maintain efficient data pipelines, ETL processes, and data warehousing solutions.
- Proficiency in Python and SQL.
- Demonstrable expertise in Google Cloud Platform (e.g., BigQuery, BQ Sharing (Analytics Hub), Cloud Functions, Dataflow, Looker Studio) to build scalable and secure data solutions.
- Other cloud-based technologies such as Windows Azure, AWS are desirable.
- Hands-on experience with marketing APIs: Google Marketing Platform, Google Ads, Social platforms.
- Familiarity with Google Marketing Products integration, including Google Analytics, CM360, SA360, and DV360.
- Experience with attribution modelling and propensity modelling.
- Understanding of paid media campaign insights and optimization.
- Proven ability in customer segmentation, profiling and activation.
- Collaborate with marketing teams to design and implement targeted customer segmentation and activation strategies.
- Google Cloud Certified Professional Data Engineer certification is highly desirable.
Pay range and compensation package
Excellent package on offer.
Data Engineer in City of London employer: TechYard
Contact Detail:
TechYard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work with Google Cloud or data engineering. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and GCP. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering scenarios. Be ready to discuss how you've tackled challenges in data pipelines or integrations with marketing APIs. We want to see your problem-solving skills in action!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Google Cloud Platform, Python, and any relevant marketing APIs. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our needs. Let us know how you can contribute to our team at StudySmarter.
Showcase Your Projects: If you've worked on any cool projects related to data pipelines or AI agents, make sure to mention them! We love seeing real-world applications of your skills, so don’t hold back on sharing your achievements.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at TechYard
✨Know Your Tech Stack
Make sure you’re well-versed in the tools and technologies mentioned in the job description, especially Google Cloud Platform and Python. Brush up on your knowledge of BigQuery, Cloud Functions, and any relevant APIs. Being able to discuss how you've used these tools in past projects will show that you're not just familiar but also experienced.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly those related to data pipelines or integrations. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you clearly demonstrate your analytical thinking and problem-solving abilities, which are crucial for a Data Engineer.
✨Understand the Client's Needs
Research the company and its clients to understand their unique marketing challenges. Be ready to suggest how you would approach solving these issues using Google Marketing Platform tools. This shows that you can think critically about client needs and translate them into actionable solutions.
✨Prepare for Technical Questions
Expect technical questions that test your knowledge of data modelling, ETL processes, and machine learning libraries. Practice coding problems in Python and SQL, as well as discussing your experience with data accessibility and security. This preparation will help you feel confident and ready to tackle any technical challenge during the interview.
