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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.
Senior Data Engineer (SC Cleared) 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)
✨Tip Number 1
Make sure to showcase your experience with cloud-native data services, especially Microsoft Azure and its components like Data Lake and Synapse. Highlight any specific projects where you've successfully implemented these technologies, as this will resonate well with our requirements.
✨Tip Number 2
Demonstrate your leadership and mentoring skills by sharing examples of how you've supported the growth of your team members in previous roles. We value a culture of continuous improvement, so showing your commitment to developing others will set you apart.
✨Tip Number 3
Prepare to discuss your approach to building scalable data pipelines and integration workflows. Be ready to explain your thought process and the engineering best practices you follow, as this will be crucial in aligning with our delivery framework.
✨Tip Number 4
Familiarise yourself with our company’s values and recent projects. Being able to engage with clients and stakeholders effectively is key, so understanding our goals and how you can contribute will help you communicate your fit for the role.
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 your leadership and mentoring skills, as well as your ability to communicate complex ideas 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've 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. Highlight specific projects where you've 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 changing priorities in past roles and any recent technologies or methodologies you've explored to enhance your skills.
