At a Glance
- Tasks: Build scalable data infrastructure for AI-driven products and audience intelligence.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on engineering excellence and career development.
- Why this job: Make a real impact by developing cutting-edge data platforms that drive business success.
- Qualifications: Strong Python and SQL skills, with experience in modern data tools and cloud environments.
The predicted salary is between 50000 - 70000 £ per year.
Your role as a Data Engineer is a hands-on position focused on building scalable data infrastructure that powers AI-driven products and audience intelligence.
Key Responsibilities
- Data Platform & Pipeline Engineering (60%): Design, build and maintain scalable batch and near real-time pipelines across ingestion, transformation and serving layers. Build reusable data models and optimise performance, reliability and cost.
- Platform Evolution & Engineering Excellence (20%): Shape the Global:IQ data platform using best practices in architecture, tooling, CI/CD and infrastructure as code. Create reusable components and maintain clear technical documentation.
- Quality & Governance (10%): Implement robust data validation, testing, lineage and observability to ensure high-quality and trusted datasets. Support governance and privacy-conscious data handling.
- Collaboration & Enablement (10%): Partner with Data Science, MLOps, Product and commercial teams to deliver production-ready data solutions, mentor others and communicate clearly with stakeholders.
What You’ll Love About This Role
- Think Big: Build a data platform that scales with a cutting-edge AI and ML product.
- Own It: Take responsibility for production-grade data systems that power targeting, optimisation and measurement.
- Keep it Simple: Apply pragmatic engineering to deliver reliable, maintainable solutions without over-engineering.
- Better Together: Work in a highly collaborative, cross-functional team spanning technical and commercial expertise.
What Success Looks Like
- Develop a strong understanding of the Global:IQ platform and its core use cases.
- Onboard key datasets with robust ingestion and quality standards.
- Deliver reliable pipelines supporting live production use cases.
- Establish or improve data engineering standards and best practices.
- Build strong working relationships across Data, Product and commercial teams.
- Identify opportunities to improve scalability, reliability and efficiency.
What You'll Need
- Programming & Data Skills: Strong Python and SQL skills, and experience building production-grade data pipelines.
- Data Platform Experience: Hands-on experience with modern data tools (Snowflake, Airflow, dbt) and cloud environments, preferably AWS.
- Engineering Best Practice: Knowledge of CI/CD, testing, version control and infrastructure as code.
- Data Quality & Governance: Understanding of observability, validation and maintaining reliable data systems.
- Collaboration & Communication: Ability to translate business and data science needs into scalable solutions and communicate clearly with stakeholders.
- Mindset & Approach: Pragmatic, ownership-driven and curious, with a passion for building impactful data products.
Data Engineer employer: Global
Global is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for professionals looking to make a significant impact in the tech industry. With a strong emphasis on employee growth and development, you will have access to numerous opportunities to enhance your skills and advance your career while working alongside visionary leaders in a dynamic environment. Located at the forefront of technological advancement, Global offers unique advantages such as exposure to cutting-edge AI initiatives and a commitment to continuous improvement.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data engineering field. Building relationships can open doors to opportunities that aren’t even advertised.
✨Show Off Your Skills
Don’t just tell us what you can do; show us! Create a portfolio of projects that highlight your Python and SQL skills, and any experience with tools like Snowflake or Airflow. This will give you an edge and demonstrate your hands-on abilities.
✨Ace the Interview
Prepare for technical interviews by brushing up on your data pipeline knowledge and engineering best practices. Be ready to discuss how you’ve tackled challenges in past projects and how you can contribute to our data platform evolution.
✨Apply Through Our Website
Make sure to apply through our website for the best chance at landing the job! We love seeing candidates who are genuinely interested in joining our team and contributing to our mission of building impactful data products.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Data Engineer role. Highlight your experience with Python, SQL, and any data tools like Snowflake or Airflow. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for building scalable data infrastructure and how you’ve tackled similar challenges in the past. Let us know why you’re excited about joining StudySmarter!
Showcase Your Projects:If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work that demonstrate your ability to build production-grade data pipelines and your understanding of data quality and governance.
Apply Through Our Website:We encourage you to apply through our website for a smoother 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 Global
✨Know Your Data Tools
Make sure you brush up on your knowledge of modern data tools like Snowflake, Airflow, and dbt. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Python and SQL Skills
Prepare to demonstrate your programming prowess, especially in Python and SQL. You might be asked to solve a problem or optimise a query on the spot, so practice coding challenges beforehand to keep your skills sharp.
✨Understand CI/CD and Infrastructure as Code
Familiarise yourself with CI/CD practices and infrastructure as code concepts. Be prepared to explain how you've implemented these in previous roles, as this will show your commitment to engineering excellence and best practices.
✨Communicate Clearly and Collaboratively
Since collaboration is key in this role, think about examples where you've worked with cross-functional teams. Be ready to discuss how you translated complex data needs into actionable solutions and how you maintained clear communication with stakeholders.
