Senior Data Engineer (SC Cleared)

JR United Kingdom; Exeter; On-site; GBP 45,000 - 65,000; Full time

Job summary

A leading consulting group seeks a Data Engineering Lead for their Exeter office. The successful candidate will spearhead data projects, prioritizing solution scalability and security while mentoring diverse teams. Candidates should possess strong expertise in data engineering tools, notably within Microsoft Azure, and effective communication skills to translate technical concepts to stakeholders.

Qualifications

• Direct experience with data engineering processes and tools.
• Strong knowledge of cloud platforms, specifically Microsoft Azure.
• Experience with automated testing and data pipeline development.

Responsibilities

• Lead complex data engineering projects ensuring quality and scalability.
• Design and implement data pipelines and workflows across various platforms.
• Mentor teams and foster a culture of technical excellence.

Skills

Data engineering

Cloud-native data services

Python

SQL

DevOps principles

Data governance

Agile methodologies

Tools

Microsoft Azure

Azure Data Factory

Talend

dbt

Job description

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Client:

CALIO Consulting Group (CCG)

Location:

exeter, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

3

Posted:

10.06.2025

Expiry Date:

25.07.2025

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Job Description:

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.
• 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.