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For Companies At a Glance
- Tasks: Lead complex data engineering projects and design scalable data pipelines.
- Company: Join a forward-thinking firm focused on innovative data solutions.
- Benefits: Enjoy flexible working options, continuous learning opportunities, and a collaborative culture.
- Why this job: Make an impact by shaping data solutions and mentoring teams in a dynamic environment.
- Qualifications: Experience with Azure, Python, SQL, and strong communication skills required.
- Other info: SC clearance is essential for this role.
The predicted salary is between 48000 - 72000 £ per year.
Key Responsibilities
- Lead the technical delivery of complex data engineering projects, ensuring solutions are scalable, secure, and aligned with our delivery framework and client goals.
- Design and build high-quality data pipelines and integration workflows, setting the technical direction and ensuring engineering best practices are followed throughout the development lifecycle.
- Collaborate with multidisciplinary teams, including a wide range of other roles, to shape solutions that meet both technical and business requirements.
- Mentor and support data engineering teams, fostering a culture of continuous improvement, knowledge sharing, and technical excellence.
- Support testing activities by ensuring pipelines are testable, observable, and reliable; work with QA and analysts to define test strategies, implement automated tests, and validate data quality and integrity.
- Contribute to technical planning, including estimation, risk assessment, and defining delivery approaches for client engagements and new opportunities.
- Engage with clients and stakeholders, translating data requirements into technical solutions and communicating complex ideas clearly and effectively.
- Champion engineering standards, contributing to the development and adoption of data engineering guidelines, design patterns, and delivery methodologies that contribute to our delivery framework.
- Stay current with emerging technologies, evaluating their relevance and potential impact, and promoting innovation within the firm and clients.
- Contribute to internal capability building, helping shape data engineering practices, tools, and frameworks that enhance delivery quality and efficiency.
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.
Technologies, Methodologies and Frameworks:
- Direct delivery experience using cloud-native data services, specifically in Microsoft Azure, Fabric, Dataverse, Synapse, Data Lake, Purview.
- Deep expertise in data engineering tools and practices, including Python, SQL, and modern ETL/ELT frameworks (e.g., Azure Data Factory, Talend, dbt).
- 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.
Contact Detail:
CALIO Consulting Group (CCG) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer (SC Cleared)
✨Tip Number 1
Make sure to showcase your experience with cloud-native data services, especially Microsoft Azure and its various components. Highlight any specific projects where you've designed and implemented scalable data pipelines, as this will resonate well with our technical requirements.
✨Tip Number 2
Demonstrate your leadership and mentoring skills by discussing instances where you've supported the growth of engineering teams. We value a culture of continuous improvement, so examples of how you've fostered knowledge sharing will be beneficial.
✨Tip Number 3
Prepare to discuss your approach to collaborating with multidisciplinary teams. Being able to articulate how you've translated complex data requirements into technical solutions will show that you can effectively engage with both technical and non-technical stakeholders.
✨Tip Number 4
Stay updated on emerging technologies and be ready to share your insights on their relevance to data engineering. Showing your commitment to innovation and continuous learning will align with our values and demonstrate your proactive mindset.
We think you need these skills to ace Senior Data Engineer (SC Cleared)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with cloud-native services like Microsoft Azure and tools such as Python and SQL. Emphasise any leadership or mentoring roles you've had, as these are key for this position.
Craft a Compelling Cover Letter: In your cover letter, clearly articulate your understanding of the role and how your skills align with the responsibilities outlined. Mention specific projects where you've led technical delivery or collaborated with multidisciplinary teams to showcase your experience.
Showcase Technical Skills: Include a section in your application that details your technical competencies, especially in areas like data pipeline design, ETL/ELT frameworks, and DevOps principles. Use concrete examples to demonstrate your expertise and problem-solving abilities.
Highlight Continuous Learning: Mention any recent training, certifications, or self-directed learning you've undertaken related to emerging technologies in data engineering. This shows your commitment to staying current and your proactive approach to professional development.
How to prepare for a job interview at CALIO Consulting Group (CCG)
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with cloud-native data services, particularly in Microsoft Azure. Highlight specific projects where you designed and implemented scalable data pipelines, and be ready to explain the tools and frameworks you used, such as Python and SQL.
✨Demonstrate Leadership and Mentoring Skills
Since the role involves mentoring teams, share examples of how you've supported the growth of others in your previous positions. Discuss any initiatives you've led that fostered a culture of continuous improvement and knowledge sharing.
✨Communicate Clearly with Stakeholders
Practice articulating complex technical concepts in simple terms. You may be asked to explain how you would translate data requirements into technical solutions, so think about how you can effectively communicate with both technical and non-technical stakeholders.
✨Emphasise Adaptability and Continuous Learning
The company values self-motivated individuals who are quick to learn new tools and technologies. Be ready to discuss how you've adapted to new challenges in the past and your approach to staying current with emerging technologies in the data engineering field.
