At a Glance
- Tasks: Design and implement innovative data solutions in a secure environment.
- Company: A leading organisation focused on security and compliance.
- Benefits: Competitive salary, professional development, and a supportive work culture.
- Other info: Active security clearance required; inclusive recruitment process.
- Why this job: Make a real impact with cutting-edge data technologies and AI-driven solutions.
- Qualifications: Experience in data architecture, entity resolution, and MDM is essential.
The predicted salary is between 60000 - 80000 £ per year.
Overview
Data Architect with active security clearance. The role involves working with large-scale data environments to improve data quality, establish trusted master records, and enable AI-driven data matching. Ideal for an experienced Data Architect with deep expertise in Entity Resolution, Master Data Management (MDM), and large-scale data integration, delivering high-quality solutions that meet customer expectations.
Responsibilities
- Lead the design and implementation of enterprise Entity Resolution solutions across multiple data sources.
- Design scalable Master Data Management (MDM) architectures and Golden Record models.
- Develop record linkage, matching, deduplication, clustering, and survivorship strategies.
- Define entity hierarchies, data standards, and data governance processes.
- Monitor and improve matching accuracy, precision, recall, and platform scalability.
- Support AI and machine learning approaches to improve entity matching and data quality.
- Collaborate with technical and business stakeholders to deliver high-quality data solutions.
- Produce architecture documentation and ensure delivery against agreed programme milestones.
Qualifications
- Proven experience as a Data Architect delivering large-scale data solutions.
- Strong expertise in Entity Resolution and Master Data Management (MDM).
- Experience designing Golden Record models, entity hierarchies, and data governance frameworks.
- Strong knowledge of record linkage, deduplication, clustering, and matching algorithms.
- Experience implementing survivorship rules, standardisation, and data merging strategies.
- Experience working with AI and Machine Learning techniques for entity matching is highly desirable.
- Strong understanding of enterprise data architecture, data quality, and large-scale data integration.
- Excellent stakeholder engagement, communication, and analytical skills.
- Experience delivering fixed-scope projects to challenging timescales.
Notes
Active security clearance is required. Some information about the employer and security considerations is included for context. The organisation holds Enhanced Government Security Accreditation and is active in delivering security-cleared talent to organisations that require high levels of security, compliance and assurance.
If you require any adjustments or support during the recruitment process, please let us know and we will work with you to ensure a fair and accessible experience.
Data Architect - SC Cleared in City of Westminster employer: Onyx-Conseil
Onyx-Conseil is an excellent employer for those seeking a dynamic and rewarding career in infrastructure engineering. With a strong focus on employee development, the company offers numerous growth opportunities, a collaborative work culture, and the chance to work on impactful projects in secure environments. Located in Salford, employees benefit from a vibrant community and access to cutting-edge technology, making it an ideal place for professionals looking to enhance their skills and contribute to meaningful projects.
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We think this is how you could land Data Architect - SC Cleared in City of Westminster
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We think you need these skills to ace Data Architect - SC Cleared in City of Westminster
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
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