At a Glance
- Tasks: Design and implement secure, scalable data platforms for Defence and Aerospace programmes.
- Company: Join a leading tech firm in the Defence and Aerospace sector.
- Benefits: Hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Active SC Clearance required; dynamic environment with significant career advancement.
- Why this job: Be a technical leader driving innovation in data engineering and analytics.
- Qualifications: 7+ years in Data Engineering with strong cloud platform expertise.
The predicted salary is between 63000 - 77000 £ per year.
Location
Reading (Hybrid Working Available)
Security Clearance
Active SC Clearance Required
Industry Experience
Aerospace, Defence, MOD or Defence Digital environments essential
About the Role
We are seeking a highly capable
Principal Data Engineer to join the Secure Digital Platform (SDP) Data & Integration team, supporting critical Defence and Aerospace programmes.
This role is responsible for the design, implementation, governance and continuous improvement of enterprise-scale data platforms, pipelines and architectures.
As a technical leader, you will drive the development of secure, scalable and resilient data solutions that enable data-driven decision-making, advanced analytics and digital transformation within highly regulated environments.
Working closely with architects, engineering teams, business stakeholders and delivery functions, you will establish engineering best practices, modernise data platforms, and lead the adoption of Data Ops and cloud-native technologies.
Key Responsibilities
- Data Architecture & Engineering
- Design and maintain secure, scalable and resilient enterprise data architectures and platforms.
- Lead the development of enterprise data pipelines, integration frameworks and data products.
- Establish and enforce data engineering standards, architectural patterns and best practices.
- Drive the adoption of modern cloud-native data services and architectures.
- Support data platform modernisation and cloud migration initiatives.
- Ensure platform reliability, performance and scalability.
- Data Ops & Automation
- Implement Data Ops and Dev Ops methodologies to improve deployment efficiency and operational reliability.
- Develop and maintain CI/CD capabilities for data platforms and pipelines.
- Automate testing, deployment, monitoring and recovery processes.
- Promote Infrastructure as Code (Ia C) and platform automation.
- Improve engineering efficiency through standardisation and automation.
- Data Governance & Quality
- Ensure data quality, integrity, lineage and consistency across enterprise platforms.
- Establish monitoring and alerting for data quality and platform performance.
- Support compliance with security, regulatory and information governance requirements.
- Enable metadata management, auditability and data stewardship capabilities.
- Drive adoption of data governance frameworks and standards.
- Strategic Leadership
- Provide technical leadership, mentoring and coaching across data engineering teams.
- Align data engineering initiatives with organisational and programme objectives.
- Support delivery of advanced analytics, AI and machine learning capabilities.
- Influence technology decisions, architecture roadmaps and investment priorities.
- Build strong relationships with business and technical stakeholders.
- Planning & Delivery
- Prioritise high-value initiatives and technical improvements.
- Manage dependencies across multiple projects and programmes.
- Provide technical oversight and delivery assurance.
- Monitor and mitigate technical risks and delivery challenges.
- Support effective resource planning and engineering capacity management.
Skills & Experience
- Active SC Clearance.
- Experience delivering data solutions within MOD, Defence Digital, Aerospace, National Security or similarly regulated environments.
- Minimum 7 years' experience in Data Engineering, Data Platform Development or related disciplines.
- Strong expertise designing and implementing enterprise-scale data architectures.
- Extensive experience with cloud data platforms including Microsoft Azure, AWS or Google Cloud.
- Strong proficiency in SQL, Python, Spark and modern data processing frameworks.
- Experience building and managing ETL/ELT pipelines and streaming data solutions.
- Practical experience with Data Ops, Dev Ops, CI/CD pipelines and Infrastructure as Code.
- Strong understanding of data modelling, data warehousing and master data management principles.
- Experience with data governance, metadata management and data quality frameworks.
- Excellent stakeholder engagement, communication and leadership skills.
- Strong analytical, troubleshooting and problem-solving capabilities.
- Experience working in Agile delivery environments.
- Professional cloud certifications across Azure, AWS or GCP.
- Experience with Azure Data Factory, Databricks, Microsoft Fabric, Snowflake, Apache Airflow or similar technologies.
- Knowledge of AI/ML platforms and MLOps practices.
- Experience with graph databases and knowledge engineering solutions.
- Experience implementing Data Mesh or Data Fabric architectures.
- Knowledge of Defence security standards and classified environments.
- TOGAF, DAMA CDMP or equivalent industry-recognised certifications.
- What Success Looks Like
The successful candidate will
- Deliver secure, scalable and resilient enterprise data platforms supporting Defence and Aerospace programmes.
- Enable effective deployment of data, analytics and digital capabilities across SDP.
- Drive automation, standardisation and continuous improvement initiatives.
- Improve platform reliability, performance, governance and operational efficiency.
- Support advanced analytics, AI and machine learning capabilities.
- Act as a trusted technical leader across data engineering, platform and architecture domains.
- #J-18808-Ljbffr
Principal Data Engineer in Reading employer: LHH
LHH is an exceptional employer that prioritises employee development and engagement, particularly in the vibrant city of Exeter. With a strong focus on fostering a collaborative work culture, employees are encouraged to grow their skills and advance their careers while making a meaningful impact on organisational performance. The company offers competitive benefits and a supportive environment that values innovation and continuous improvement.
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We think you need these skills to ace Principal Data Engineer in Reading
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
