At a Glance
- Tasks: Build reliable data foundations and enhance AI systems with your data engineering expertise.
- Company: Join a forward-thinking company shaping the future of AI technology.
- Benefits: Enjoy remote work flexibility, competitive pay, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Make a real impact on AI by optimising data pipelines and ensuring data quality.
- Qualifications: 4+ years in data engineering with strong SQL and ETL/ELT skills required.
The predicted salary is between 60000 - 80000 € per year.
If you're a senior Data Engineer who thrives on precision, systems thinking, and building reliable data foundations, this is a unique opportunity to contribute directly to how the next generation of AI systems reason about data infrastructure, pipelines, and analytics workflows.
We're looking for experienced Data Engineers who understand modern data stacks, ETL/ELT architecture, orchestration, data modeling, warehouse design, quality validation, governance, and production-scale reliability. Your work will help strengthen how AI models reason through complex data engineering scenarios, identify technical errors, and communicate implementation guidance clearly.
Your Profile
- 4+ years of professional experience in data engineering, with significant hands-on work designing, building, and maintaining production-grade data pipelines.
- Deep knowledge of SQL, data modeling, ETL/ELT architecture, orchestration frameworks, warehouse/lakehouse patterns, and modern data stack tools such as dbt, Airflow, Snowflake, BigQuery, Databricks, Fivetran, or similar platforms.
- Strong understanding of distributed data systems, batch and streaming workflows, schema design, data validation, data observability, lineage, and pipeline reliability.
- Proven experience optimizing complex SQL queries, troubleshooting data quality issues, designing scalable transformations, and supporting analytics or machine learning-ready datasets.
- Demonstrated experience in translating ambiguous business or technical requirements into reliable data models, pipeline designs, and implementation plans.
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Statistics, Engineering, or a related technical field; equivalent professional experience will also be considered.
- Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
Key Responsibilities
- Evaluate AI-generated answers to data engineering prompts for technical accuracy, completeness, clarity, and real-world feasibility.
- Challenge advanced language models with complex Data Engineer scenarios involving SQL, Python, ETL/ELT design, orchestration, warehousing, data modeling, and pipeline reliability.
- Review and refine AI-generated prompts, responses, rubrics, and reference answers to ensure they reflect senior-level data engineering judgment.
- Provide structured feedback that identifies incorrect assumptions, missing constraints, weak reasoning, inefficient implementations, or unsafe recommendations.
- Shape AI communication standards by helping models explain data architecture, debugging steps, tradeoffs, and implementation patterns clearly and responsibly.
- Support benchmarking efforts by evaluating model performance across realistic data engineering workflows, edge cases, and failure modes.
- Develop and review high-quality examples that demonstrate strong reasoning around pipeline design, data quality checks, data contracts, schema evolution, and system scalability.
Data Engineer – Remote in London employer: YO IT CONSULTING
As a remote employer, we offer Data Engineers the flexibility to work from anywhere while contributing to cutting-edge AI systems that shape the future of data infrastructure. Our collaborative work culture fosters innovation and continuous learning, providing ample opportunities for professional growth and development in a rapidly evolving field. Join us to be part of a team that values precision, creativity, and the pursuit of excellence in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer – Remote in London
✨Tip Number 1
Network like a pro! Reach out to fellow Data Engineers on LinkedIn or join relevant online communities. Engaging in conversations can lead to job opportunities that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, SQL queries, and any projects you've worked on. This gives potential employers a tangible sense of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering scenarios. Practice explaining your thought process when tackling complex problems, as this will demonstrate your expertise and systems thinking.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes the application process smoother for everyone involved.
We think you need these skills to ace Data Engineer – Remote in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with SQL, ETL/ELT architecture, and any relevant tools like dbt or Airflow. 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 experience aligns with our mission at StudySmarter. Keep it concise but impactful!
Showcase Your Projects:If you've worked on interesting data projects, don't hold back! Include links or descriptions of your work that demonstrate your ability to design and maintain production-grade data pipelines. We love seeing real-world applications of your skills.
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 the role. Plus, it shows you’re keen on joining the StudySmarter team!
How to prepare for a job interview at YO IT CONSULTING
✨Know Your Data Stack
Make sure you’re well-versed in the modern data stack tools mentioned in the job description, like dbt, Airflow, and Snowflake. Brush up on your SQL skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data engineering, especially around pipeline reliability and data quality issues. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your problem-solving abilities.
✨Understand AI Integration
Since this role involves working with AI systems, be prepared to talk about any experience you have with AI data training or evaluating AI-generated content. Think of examples where you’ve had to ensure technical accuracy and clarity in data models.
✨Ask Insightful Questions
At the end of the interview, don’t shy away from asking questions that show your interest in the company’s data strategies and future projects. This not only demonstrates your enthusiasm but also helps you gauge if the role aligns with your career goals.
