Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and maintain data pipelines for efficient data ingestion and transformation.
- Company: Join Nixor, a growing data and analytics function with a collaborative culture.
- Benefits: Enjoy a competitive salary, great benefits, and a supportive work environment.
- Other info: Collaborate with experienced leaders and grow your skills in a dynamic setting.
- Why this job: Make an impact by working on innovative data platforms and optimising workflows.
- Qualifications: Experience in data engineering, ETL/ELT pipelines, and proficiency in SQL and Python.
The predicted salary is between 50000 - 60000 £ per year.
Nixor are proud to present an opportunity for a Data Engineer to join a growing data and analytics function, supporting the delivery of reliable, scalable, and high-quality data solutions. This role is critical in enabling data-driven decision-making by ensuring data is efficiently ingested, transformed, and made available across the organisation. The Data Engineer will work closely with the Data Architecture Lead and wider analytics teams to implement agreed architectures and continuously optimise data workflows for performance and reliability.
Key Responsibilities
- Be responsible for building and maintaining data pipelines, ensuring efficient data ingestion, transformation, and delivery.
- Implement the architecture defined by the Data Architecture Lead, aligning with agreed standards, patterns, and best practices.
- Optimise data workflows to improve performance, scalability, and reliability.
- Integrate data from various sources — including internal systems, client data, and third-party data — into the organisation’s central data platform.
- Ingest data from APIs, relational and non-relational databases, and flat files.
- Ensure data quality, consistency, and integrity across all pipelines.
- Monitor and troubleshoot data pipelines, resolving issues proactively.
- Collaborate with analytics, engineering, and product teams to understand data requirements.
- Contribute to documentation and continuous improvement of data engineering processes.
Skills & Experience
- Proven experience in a Data Engineer or similar role.
- Strong experience designing and building ETL/ELT pipelines.
- Experience working with cloud-based data platforms and data warehouses.
- Proficiency in SQL and at least one programming language commonly used in data engineering (e.g. Python).
- Experience integrating data from APIs, databases, and flat file sources.
- Understanding of data modelling, performance optimisation, and reliability best practices.
- Strong problem‑solving skills and attention to detail.
Why Join
- Opportunity to work on impactful data platforms and pipelines.
- Clear architectural direction and collaboration with experienced data leaders.
- Supportive environment focused on engineering quality and best practice.
- Competitive salary and benefits package.
Data Engineer employer: My Agency
Contact Detail:
My Agency Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. 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 pipelines, ETL processes, and any projects you've worked on. This gives potential employers a tangible look at what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s data architecture. Be ready to discuss how you would optimise workflows and tackle real-world data challenges they face.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with ETL/ELT pipelines, cloud-based platforms, and any relevant programming skills. We want to see how your background aligns with what we're looking for!
Showcase Your Projects: Include specific projects where you've built or optimised data pipelines. This gives us a clear picture of your hands-on experience and problem-solving skills. Don't be shy about sharing your successes!
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. Explain why you're interested in the role and how you can contribute to our data and analytics function. We appreciate straightforward communication!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. We can't wait to hear from you!
How to prepare for a job interview at My Agency
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals. Be ready to discuss ETL/ELT processes, data pipelines, and the tools you’ve used in the past. Nixor will likely want to see how well you understand the architecture and best practices in data management.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in previous roles and how you resolved them. Highlight your attention to detail and your approach to troubleshooting data pipelines, as this is crucial for the role.
✨Familiarise Yourself with Their Tech Stack
Research the cloud-based platforms and programming languages that Nixor uses. If they mention specific technologies in the job description, make sure you can speak to your experience with them, especially SQL and Python.
✨Collaborate and Communicate
Since the role involves working closely with various teams, be prepared to discuss how you’ve collaborated in the past. Share examples of how you’ve gathered data requirements from stakeholders and contributed to documentation, as effective communication is key.