Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a dynamic team to build and optimise data pipelines and solutions.
- Company: Work with a leading consultancy known for innovative data and analytics solutions.
- Benefits: Enjoy opportunities for remote work, professional growth, and a supportive team culture.
- Why this job: Be part of exciting projects that make a real impact while developing your skills.
- Qualifications: Experience with Azure tools, programming in SQL and Python, and strong communication skills required.
- Other info: Open to all levels, from aspiring engineers to seasoned professionals ready for leadership.
The predicted salary is between 43200 - 72000 £ per year.
We’re working with a globally recognised consultancy that delivers cutting-edge digital, data, and analytics solutions to some of the most complex infrastructure projects across the UK and beyond. With a strong commitment to technical excellence, inclusion, and client impact, they partner with high-profile organisations to help them unlock the full potential of their data assets.
Due to continued growth and demand for their data services, they are expanding their specialist engineering team and seeking talented Data Engineering Consultants at various seniority levels — from experienced engineers to those ready to step into leadership roles.
The Role
As a Data Engineering Consultant, you will:
- Collaborate with stakeholders across development, analytics, and business teams to define and implement components of the data landscape in line with strategic data goals.
- Translate business and end-user needs into robust technical solutions, delivery plans, and architectural designs.
- Build and maintain highly automated, scalable data pipelines using modern cloud-based tools.
- Identify and resolve data quality and pipeline performance issues to ensure stability and integrity.
- Contribute to the design and deployment of data lakes, warehouses, and streaming architectures.
- Participate in mentoring and upskilling junior team members, supporting a high-performance, inclusive team culture.
- Continuously look for opportunities to improve delivery methods, introduce new technologies, and drive technical innovation across client projects.
- Document processes and contribute to internal knowledge repositories and best practice libraries.
Key Skills & Experience
- Strong hands-on experience with Azure tooling, including: Databricks, Data Factory, Data Lake, and Synapse (or similar data warehouse tools).
- Azure Analysis Services or comparable BI tooling.
- Solid programming capability in: SQL, Python, Spark, and ideally DAX.
- Familiarity with CI/CD, Git, and modern DevOps practices (preferably in Azure DevOps).
- Excellent communication skills — able to clearly explain technical concepts to both technical and non-technical audiences.
- Ability to operate in a client-facing environment, contributing to multi-disciplinary teams and complex programmes.
- Ideally, experience with containerisation technologies such as Docker and Kubernetes.
- Exposure to Kimball data modeling, data architecture, and performance optimisation.
- Experience delivering end-to-end solutions involving Azure data platform components.
Data Engineer employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with Azure tools like Databricks and Data Factory. Being able to discuss your hands-on experience with these technologies during interviews will show that you're not just familiar with the theory but can apply it in real-world scenarios.
✨Tip Number 2
Brush up on your programming skills, especially in SQL and Python. Prepare to demonstrate your coding abilities through practical tests or discussions, as this is a key requirement for the role.
✨Tip Number 3
Highlight any experience you have with CI/CD and DevOps practices, particularly in Azure DevOps. Be ready to share examples of how you've implemented these practices in past projects to improve efficiency.
✨Tip Number 4
Showcase your communication skills by preparing to explain complex technical concepts in simple terms. This will be crucial in a client-facing environment where you need to collaborate with both technical and non-technical stakeholders.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of a Data Engineering Consultant. Familiarise yourself with the key skills mentioned in the job description, such as Azure tooling and programming languages.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job description. Emphasise your hands-on experience with Azure tools, programming capabilities, and any client-facing roles you've had.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the consultancy's goals. Mention specific projects or experiences that demonstrate your ability to deliver technical solutions and work collaboratively.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for spelling and grammatical errors, and ensure that all information is clear and concise. A polished application reflects your attention to detail.
How to prepare for a job interview at Xcede
✨Showcase Your Technical Skills
Make sure to highlight your hands-on experience with Azure tools like Databricks and Data Factory. Be prepared to discuss specific projects where you've built data pipelines or resolved data quality issues, as this will demonstrate your technical expertise.
✨Communicate Clearly
Since the role involves explaining technical concepts to non-technical stakeholders, practice articulating your thoughts clearly. Use simple language to describe complex ideas, and be ready to provide examples of how you've done this in past roles.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss challenges you've faced in previous projects, particularly around data pipeline performance or quality issues. Highlight your approach to identifying and resolving these problems, showcasing your analytical skills and innovative thinking.
✨Emphasise Team Collaboration
As a Data Engineering Consultant, you'll need to work closely with various teams. Share experiences where you've collaborated effectively with others, mentored junior team members, or contributed to a positive team culture, as this will show your ability to thrive in a multi-disciplinary environment.
