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For Companies At a Glance
- Tasks: Lead complex data engineering projects and design high-quality data pipelines.
- Company: Join a forward-thinking firm focused on innovative data solutions.
- Benefits: Enjoy flexible working options, continuous learning opportunities, and a supportive team culture.
- Why this job: Make an impact by shaping data solutions and mentoring future engineers in a collaborative environment.
- Qualifications: Strong communication skills, experience with cloud-native services, and a passion for data engineering required.
- Other info: SC clearance is essential; stay ahead with emerging technologies and contribute to internal capability building.
The predicted salary is between 43200 - 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.
Senior Data Engineer (SC Cleared) (United Kingdom) employer: CALIO Consulting Group (CCG)
Contact Detail:
CALIO Consulting Group (CCG) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer (SC Cleared) (United Kingdom)
✨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 successfully implemented these technologies, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Emphasise your leadership and mentoring skills during conversations or interviews. Be prepared to share examples of how you've supported the growth of your team members and fostered a culture of continuous improvement in previous roles.
✨Tip Number 3
Engage with our community on platforms like LinkedIn or relevant forums. Share insights about data engineering trends and best practices, which can help you build connections and demonstrate your passion for the field.
✨Tip Number 4
Stay updated on emerging technologies and be ready to discuss how they could impact data engineering. Showing that you're proactive about learning and adapting to new tools will set you apart from other candidates.
We think you need these skills to ace Senior Data Engineer (SC Cleared) (United Kingdom)
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 well as your ability to communicate technical concepts clearly.
Craft a Compelling Cover Letter: In your cover letter, address how your skills align with the key responsibilities of the role. Mention specific projects where you led technical delivery or collaborated with multidisciplinary teams, showcasing your problem-solving abilities and commitment to continuous improvement.
Showcase Relevant Projects: Include examples of past projects that demonstrate your expertise in building scalable data pipelines and integration workflows. Highlight your experience with data governance and quality frameworks, as well as any innovative solutions you've implemented.
Prepare for Technical Questions: Anticipate technical questions related to data engineering practices, cloud services, and DevOps principles. Be ready to discuss your approach to testing, monitoring, and ensuring data quality, as well as how you stay current with emerging technologies.
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 and related tools. Highlight specific projects where you've designed and implemented scalable data pipelines, as this will demonstrate your hands-on knowledge and ability to deliver complex solutions.
✨Communicate Clearly and Effectively
As a Senior Data Engineer, you'll need to articulate technical concepts to both technical and non-technical stakeholders. Practice explaining your past projects and the technologies used in simple terms, ensuring you can convey complex ideas clearly during the interview.
✨Demonstrate Leadership and Mentoring Skills
Prepare examples of how you've mentored or supported your team in previous roles. Discuss how you've fostered a culture of continuous improvement and knowledge sharing, as this aligns with the responsibilities of the position and shows your capability to lead and inspire others.
✨Emphasise Adaptability and Problem-Solving
Be ready to discuss situations where you've had to adapt to shifting priorities or solve complex problems creatively. Share specific examples that highlight your critical thinking skills and your proactive approach to overcoming challenges in data engineering projects.
