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- Tasks: Join us as a Data Engineer or Senior Data Engineer, working on innovative data solutions.
- Company: Be part of a forward-thinking company that values collaboration and continuous learning.
- Benefits: Enjoy a permanent role with opportunities for remote work and professional development.
- Why this job: Make an impact by solving real-world problems with cutting-edge technology in a supportive team environment.
- Qualifications: Strong skills in Python, SQL, and cloud data services are essential; leadership experience is a plus.
- Other info: Roles require SC clearance; ideal for those passionate about data engineering in dynamic sectors.
The predicted salary is between 48000 - 84000 £ per year.
We have two roles available: Senior Data Engineer and Data Engineer. Both roles are permanent positions.
Location: To be confirmed.
Clearance: SC
These roles require the following:
- Essential competencies
- Strong communicator, able to clearly articulate technical concepts to both technical and non-technical stakeholders.
- Confident working independently or as part of a collaborative, cross-functional team.
- Skilled at building trust with clients and colleagues, with a consultative and solution-focused approach.
- Demonstrated leadership and mentoring capabilities, supporting the growth and development of engineering teams.
- Organised and adaptable, with excellent time management and the ability to respond to shifting priorities.
- Self-motivated, proactive, and committed to continuous learning and improvement.
- Creative problem-solver with the ability to think critically and deliver innovative, practical solutions.
- Team-oriented, with a positive attitude and a strong sense of ownership and accountability.
- Deep/Solid expertise in data engineering tools and practices, including Python, SQL, and modern ETL/ELT frameworks (e.g., Azure Data Factory, Talend, dbt).
- Direct delivery experience using cloud-native data services, specifically in Microsoft Azure, Fabric, Dataverse, Synapse, Data Lake, Purview.
- Experience designing and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB).
- Familiarity with data governance, metadata management, and data quality frameworks.
- Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring.
- Solid understanding of data security and compliance best practices, including secure data handling and regulatory requirements (e.g., Secure by design).
- Comfortable working in agile, multi-disciplinary teams, contributing across the full delivery lifecycle and supporting continuous improvement.
- Adaptable and quick to learn new tools, frameworks, and technologies to meet the needs of diverse client projects.
- Experience working in secure customer environments.
- Familiarity with working in government or defence sectors, or other complex public sector environments.
- Industry recognised Technical Qualifications (e.g., Fabric Data Engineer Associate, Microsoft Azure Data Engineer, Databricks, dbt).
- Knowledge and experience of delivering AI-based solutions.
- Proficiency in Power BI, including data modelling, DAX, and building interactive dashboards and reports that support data-driven decision-making.
Data Engineer/Senior Data Engineer Opportunities employer: ComXps
Contact Detail:
ComXps Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer/Senior Data Engineer Opportunities
✨Tip Number 1
Make sure to brush up on your communication skills. As a Data Engineer, you'll need to explain complex technical concepts to both technical and non-technical stakeholders. Practising how to articulate your thoughts clearly can set you apart during interviews.
✨Tip Number 2
Showcase your experience with cloud-native data services, especially Microsoft Azure. Familiarise yourself with the specific tools mentioned in the job description, like Azure Data Factory and Synapse, and be ready to discuss your hands-on experience with them.
✨Tip Number 3
Highlight any leadership or mentoring experiences you've had. The role requires someone who can support the growth of engineering teams, so sharing examples of how you've guided others can demonstrate your suitability for the position.
✨Tip Number 4
Be prepared to discuss your problem-solving skills and adaptability. The job calls for creative solutions and the ability to respond to shifting priorities, so think of specific instances where you've successfully navigated challenges in your previous roles.
We think you need these skills to ace Data Engineer/Senior Data Engineer Opportunities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data engineering tools and practices, especially Python, SQL, and cloud-native services like Microsoft Azure. Use specific examples to demonstrate your skills in building scalable data pipelines and your familiarity with ETL/ELT frameworks.
Craft a Compelling Cover Letter: In your cover letter, emphasise your strong communication skills and ability to articulate technical concepts to both technical and non-technical stakeholders. Mention your leadership and mentoring capabilities, as well as your proactive approach to continuous learning.
Showcase Relevant Projects: Include details of any relevant projects you've worked on that demonstrate your problem-solving abilities and experience with data governance, metadata management, and DevOps principles. Highlight any work done in secure environments or within the government sector if applicable.
Prepare for Technical Questions: Be ready to discuss your technical expertise during interviews. Prepare to explain your experience with data security best practices, compliance requirements, and how you've applied agile methodologies in previous roles. This will show your depth of knowledge and adaptability.
How to prepare for a job interview at ComXps
✨Showcase Your Communication Skills
As a Data Engineer, you'll need to explain complex technical concepts to various stakeholders. Practice articulating your past projects and how you communicated with both technical and non-technical team members.
✨Demonstrate Your Problem-Solving Abilities
Prepare examples of challenges you've faced in data engineering and how you creatively solved them. Highlight your critical thinking skills and your approach to delivering practical solutions.
✨Highlight Your Technical Expertise
Be ready to discuss your experience with Python, SQL, and cloud-native services like Azure. Familiarise yourself with the specific tools mentioned in the job description and be prepared to explain how you've used them in past roles.
✨Emphasise Team Collaboration
Since these roles require working in cross-functional teams, share experiences where you successfully collaborated with others. Discuss how you built trust and contributed to team success, showcasing your positive attitude and sense of ownership.
