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For Companies At a Glance
- Tasks: Design and define data models that drive innovation in data-intensive industries.
- Company: Join a leading tech firm in London with a hybrid work culture.
- Benefits: Competitive pay, flexible working, and opportunities for professional growth.
- Why this job: Shape the future of data ecosystems and make a real impact on businesses.
- Qualifications: Experience in data modelling for cloud platforms, especially GCP and Big Query.
- Other info: Collaborate with diverse teams in a dynamic, agile environment.
The predicted salary is between 60000 - 80000 £ per year.
Location: London, UK (Hybrid-2 days from office) 6 months contract position
The Role
In this role, you will define the data blueprints and foundational models that underpin how customers in dynamic, data intensive industries operate, scale, and innovate. You will design robust, future ready data models that enable seamless integration, advanced analytics, and AI driven decision making across complex digital transformation programmes. With access to modern data platforms, high quality datasets, and leading modelling frameworks, you will guide engineering, analytics, and architecture teams in building secure, scalable, and well governed data structures. This role empowers you to shape end to end data ecosystems accelerating delivery, enhancing data clarity, strengthening operational resilience, and driving organisations toward a more insight rich, data enabled future.
Your responsibilities:
- Define and maintain conceptual, logical, and physical data models that accurately reflect business processes and support analytics, AI/ML, and operational needs.
- Translate business requirements into robust data entities, attributes, relationships, and constraints; ensure traceability from requirements to models.
- Establish and enforce GDM modelling standards and naming conventions (e.g., normalization, dimensional/star/snowflake patterns, data vault where appropriate).
- Design dimensional models (facts, dimensions, hierarchies, slowly changing dimensions) for BI/analytics and performance at scale.
- Create and manage canonical data models and semantic layers to enable consistent metrics and self-service analytics across domains.
- Ensure data quality by designing integrity rules, reference/master data relationships, and validation checks embedded in pipelines.
- Optimise models for performance and cost (partitioning, clustering, indexing, compression, surrogate keys, distribution strategies).
- Drive data integration design across sources (CDC, event streaming, APIs), mapping source-to-target, resolving conflicts, and handling historical changes.
- Support AI/ML readiness by modelling features, aggregations, and histories; collaborate on feature stores and model input/output schemas.
- Embed privacy and security requirements into models (PII classification, minimisation, masking, role-based access, retention, and residency).
Your Profile
Essential skills/knowledge/experience:
- Proven experience delivering conceptual, logical, and physical data models for cloud data platforms, ideally GCP.
- Strong hands-on modelling for Big Query (analytical/columnar patterns, denormalization strategy, partitioning & clustering considerations).
- Expertise in data modelling approaches: 3NF, dimensional (Kimball), Data Vault, and hybrid patterns for Lakehouse designs.
- Maintain versioned model artefacts (ERDs, schema scripts, JSON/YAML specs) and change logs; manage controlled evolution of models.
- Ability to translate banking domain requirements (Customer, Accounts, Payments, Credit, Risk, Finance) into scalable canonical models.
- Strong understanding of Big Query performance and cost optimisation impacts driven by modelling choices (query patterns, storage, scan costs).
- Experience designing data products for analytics and reporting with trusted definitions (facts, dimensions, SCD, conformed dimensions).
- Strong knowledge of data governance: metadata management, lineage, stewardship, data quality rules, and critical data elements.
- Proficiency with data modelling tools such as ER/Studio, Power Designer, ERWin, SQL Developer Data Modeler, or equivalent cloud-native tools.
- Familiarity with GCP ecosystem integration (e.g., Cloud Storage, Dataflow/Dataproc, Pub/Sub) and how ingestion patterns influence modelling.
Desirable skills/knowledge/experience:
- Experience supporting regulatory, risk, and audit needs through traceability, controlled definitions, and clear lineage to source systems.
- Capability in defining and enforcing enterprise standards (naming conventions, reference data, code sets, data contracts).
- Experience with model versioning, impact analysis, and change control across multiple downstream consumers.
- Ability to partner closely with data engineers and architects to drive physical implementation, testing, and production readiness.
- Strong communication skills to explain complex data structures to both technical and non-technical stakeholders.
- Comfortable operating in Agile delivery: contributing to user stories, acceptance criteria, design assurance, and documentation.
- Solid understanding of data modelling techniques such as normalization, denormalization, Data Vault, semantic modelling, and canonical models.
- Familiarity with master data management (MDM), reference data frameworks, and designing conformed dimensions.
- Proficiency in SQL and data profiling to validate models against source data and ensure completeness/consistency.
Data Modeller employer: DCV Technologies Limited
Contact Detail:
DCV Technologies Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeller
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the data modelling space. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data models and projects. This is your chance to shine and demonstrate how you can add value to potential employers. Make sure to include any relevant experience with GCP and Big Query.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with different data modelling techniques and how you've tackled challenges in past projects. Practice explaining complex concepts in simple terms – it’ll impress both technical and non-technical interviewers!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented data modellers like you. Plus, applying directly gives you a better chance to stand out and get noticed by our hiring team.
We think you need these skills to ace Data Modeller
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Modeller role. Highlight your experience with data modelling techniques and cloud platforms, especially GCP, as this will show us you’re a great fit for what we need.
Showcase Your Skills: Don’t just list your skills; demonstrate them! Use specific examples from your past work that relate to the responsibilities mentioned in the job description. This helps us see how you can contribute to our team.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon unless it’s relevant to the role. Make it easy for us to see your qualifications!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at DCV Technologies Limited
✨Know Your Data Models
Make sure you brush up on your knowledge of conceptual, logical, and physical data models. Be ready to discuss how you've applied these in previous roles, especially in cloud environments like GCP. Highlight your experience with Big Query and any specific modelling techniques you've used.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex data integration challenges. Think about times when you resolved conflicts or handled historical changes in data. This will demonstrate your ability to think critically and adaptively in a fast-paced environment.
✨Understand the Business Context
Familiarise yourself with the banking domain and be ready to translate business requirements into data models. Discuss how your models have supported analytics and operational needs in past projects, showing that you can align technical work with business goals.
✨Communicate Clearly
Practice explaining complex data structures in simple terms. You might encounter both technical and non-technical stakeholders during the interview, so being able to communicate effectively is key. Prepare to discuss how you've collaborated with teams in Agile settings to ensure everyone is on the same page.