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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 flexible working options, professional development, and a supportive team culture.
- Why this job: Be part of exciting projects that make a real impact on clients' data strategies.
- Qualifications: Experience with Azure tools, programming skills in SQL and Python, and strong communication abilities.
- Other info: Opportunities for mentorship and leadership roles available as you grow.
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 the specific Azure tools mentioned in the job description, such as Databricks and Data Factory. Consider building a small project or contributing to an open-source project that uses these technologies to showcase your hands-on experience.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work with Azure. Attend meetups or webinars focused on Azure data solutions to gain insights and potentially make connections that could lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with CI/CD and DevOps practices during interviews. Be ready to share examples of how you've implemented these methodologies in past projects, particularly in relation to Azure DevOps.
✨Tip Number 4
Showcase your communication skills by practising explaining complex technical concepts in simple terms. This will be crucial in a client-facing role, so consider role-playing with a friend or mentor to refine your ability to convey information clearly.
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 and any projects where you've built data pipelines or worked in a client-facing environment.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the consultancy's mission. Mention specific examples of how your skills can contribute to their projects and goals.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for any spelling or 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 how you've identified and resolved performance issues in data pipelines. Think of specific instances where your analytical skills made a significant impact on project outcomes, as this will showcase your problem-solving capabilities.
✨Emphasise Team Collaboration
This role requires working closely with various teams, so be ready to share experiences where you collaborated effectively. Highlight any mentoring or leadership roles you've taken on, as this aligns with their focus on building an inclusive team culture.
