Engineering Data Manager

Engineering Data Manager

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Raytheon

At a Glance

  • Tasks: Manage engineering data integrity and lifecycle across product development and support activities.
  • Company: Join Raytheon UK, a leader in defence and aerospace technology.
  • Benefits: Enjoy competitive salaries, flexible working, and generous holiday allowances.
  • Other info: Collaborative culture with opportunities for professional growth and community impact.
  • Why this job: Be part of a team shaping national security while advancing your career.
  • Qualifications: Degree in Engineering or related field with experience in data management.

The predicted salary is between 60000 - 80000 £ per year.

hackajob is collaborating with Raytheon to connect them with exceptional professionals for this role.

Location: Gloucester

Security Clearance Required: Baseline BPSS and SC

Duration: Permanent

Hours: 37hrs per week

At Raytheon UK, we take immense pride in being a leader in defence and aerospace technology. As an employer, we are dedicated to fuelling innovation, nurturing talent, and fostering a culture of excellence.

Joining our team means being part of an organisation that shapes the future of national security whilst investing in your growth and personal development. We provide a collaborative environment, abundant opportunities for professional development, and a profound sense of purpose in what we do.

About the role:

The Engineering Data Manager is responsible for the governance, integrity, and lifecycle management of engineering data across product development and in‑service support activities. This role ensures that product design changes, technical changes, and configuration data are accurately controlled, authorised, and maintained within approved systems in accordance with internal procedures, customer requirements, and regulatory standards.

The position plays a critical role in safeguarding product and system data integrity during the exploitation of engineering data, establishing trusted data foundations that enable advanced analytics and the responsible adoption of Artificial Intelligence technologies, including Generative AI and Large Language Models.

Skills and Experience

  • HNC/HND or Degree in Engineering, Engineering Management, or a related technical discipline.
  • Proven experience in engineering data management, configuration control, or design change management.
  • Strong understanding of product lifecycle management (PLM) concepts.
  • Experience managing design and technical change in complex engineering environments.
  • Demonstrated ability to maintain high levels of data integrity, accuracy, and traceability.
  • Strong stakeholder management and communication skills.
  • Ability to work effectively in regulated industries (e.g. aerospace, defence, automotive, rail, energy).

Desirable Skills & Experience

  • Experience with PLM/PDM systems such as Windchill, Teamcenter, or Enovia.
  • Knowledge of configuration management standards (e.g. ISO 10007, EIA‑649).
  • Familiarity with quality and regulatory frameworks (e.g. AS9100, ISO 9001).
  • Experience supporting audits, certifications, or customer data deliverables.
  • Understanding of digital thread / digital twin concepts.
  • Highly organised with strong attention to detail.
  • Analytical and methodical problem‑solver.
  • Confident in challenging non‑compliance and driving best practice.
  • Comfortable working across multiple projects and prioritising effectively.
  • Committed to continuous improvement and data excellence.

Responsibilities

Engineering Data & Integrity

  • Own and maintain the integrity of engineering data infrastructure, defining strategy and leading the technical execution of change to ensure reliable data pipelines for analytics and business needs.
  • Enable rapid improvements in Master Data quality to support effective data exploitation and the adoption of new and evolving systems.
  • Ensure raw engineering data is accurately transformed into usable data assets through effective structuring, version control, and full traceability of product definitions, including drawings, models, specifications, and Bills of Material (BOMs).
  • Support the exploitation of engineering data by ensuring data integrity underpins current and future business needs.
  • Enable and support organisational AI initiatives by providing trusted data foundations and deploying advanced technologies and tools to end users.
  • Establish and enforce data standards, naming conventions, and classification rules across engineering datasets.

Product Design Change Management Integrity

  • Design, implement and manage the end-to-end data platforms which control product design change, ensuring all changes are correctly assessed, approved, implemented, and recorded.
  • Drive the creation of scalable and efficient pipelines and processing systems for data ingestion, transformation and access.
  • Ensure design changes maintain data compliance with safety and security protocols.

Data Governance and Quality through Technical Change Control

  • Establish and enforce data management, security and compliance policies ensuring high data quality and integrity.
  • Maintain accurate change histories and configuration baselines throughout the product lifecycle.
  • Support configuration audits and design reviews by providing authoritative data sets.

Data Integrity & Assurance

  • Ensure engineering data platforms remain accurate, complete, secure, fit for purpose and align with regulatory frameworks.
  • Perform regular data quality assessments and audits to identify discrepancies or integrity risks.
  • Drive continuous improvement initiatives to reduce data errors, rework, and inefficiencies.

Cross-Functional Collaboration

  • Act as the primary interface between data sciences, analytics, engineering, manufacturing, quality, supply chain, and programme teams on data-related matters.
  • Provide expert advice on data governance, emerging techniques and technologies.
  • Support internal and external stakeholders, including customers and regulatory authorities.

Tools, Systems & Continuous Improvement

  • Manage and optimise the use of tools.
  • Support system enhancements of data processing and transformation, migrations, and process improvements.
  • Contribute to the development of engineering data management policies, procedures, and training materials.

Benefits and Work Culture

Benefits

  • Competitive salaries.
  • 25 days holiday + statutory public holidays, plus opportunity to buy and sell up to 5 days.
  • Contributory Pension Scheme (up to 10.5% company contribution).
  • Company bonus scheme (discretionary).
  • 6 times salary ‘Life Assurance’ with pension.
  • Flexible Benefits scheme with extensive salary sacrifice schemes.
  • Enhanced sick pay.
  • Enhanced family friendly policies including enhanced maternity, paternity & shared parental leave.

Work Culture

  • 37hr working week, although hours may vary depending on role.
  • Early 1.30pm finish Friday, start your weekend early!
  • A grownup flexible working culture that is output-focused.
  • Up to 5 paid days volunteering each year.

Raytheon UK is a landed company and part of the wider RTX organisation. Supporting over 35,000 jobs across 13 UK sites, RTX is helping to drive prosperity.

Raytheon

Contact Details:

Raytheon Recruitment Team

We think you need these skills to ace Engineering Data Manager

Communication Skills
Problem-Solving Skills
SQL
Python
Data Engineering
Data Pipeline Development
API Integration