XM

Global forex and CFD broker

Data Architect

Data ManagementConfirmed live in the last 24 hours

Full-timeNo salary listed

About the Job

Requirements

A Bachelor of Science or Master of Science in Computer Science, Information Technology, or a related field.
At least 3 years of experience in data modeling, data engineering, database design, or data architecture roles.
Strong expertise in conceptual, logical, and physical data modeling, with solid SQL skills.
Proficiency in Python for data-related work such as automation, prototyping, analysis, validation, data quality checks, and tooling around data pipelines and integrations.
Experience working with cloud-based data platforms and modern data warehouse or lakehouse architectures.
Good understanding of software development lifecycles, requirements analysis, and technical design best practices.
Exposure to data governance, metadata management, and data quality frameworks.
Confidence advising on ETL/ELT patterns, data integration solutions, and data orchestration technologies.

Responsibilities

Develop conceptual, logical, and physical data models, focusing on design structure, semantics, constraints, and alignment to business meaning, including physical design considerations such as indexing and partitioning.
Define and maintain reference and target data architectures, including standards and reusable patterns, across operational systems, event and streaming platforms, and analytical environments such as data warehouses and lakehouses.
Drive architectural decision-making and trade-offs involving consistency, performance, scalability, cost, operability, and security, and contribute to architecture documentation practices that capture and govern those decisions.
Support implementation of the organizational data strategy, including database design standards, data warehouse architecture, standards and guidance, and analytics platform integration.
Assist with deployment and extension of the Enterprise Data Catalogue.
Contribute to creating and maintaining architecture processes and documentation standards.
Partner with project teams as an embedded contributor, guiding schema design, physical design choices such as indexing and partitioning, data access patterns, and query optimization best practices, and support teams through design reviews and delivery.
Advise project teams on the end-to-end data product lifecycle, from platform selection through testing and implementation.
Govern changes to architectural artefacts and ensure systems conform to established data architecture guidelines.
Define data flows and integration patterns across applications and services, including operational systems, streams, and analytical platforms for batch and real-time processing, with clear ownership and information dissemination patterns.

Desired Qualifications

Experience in graph databases, vector databases or semantic search capabilities, feature stores, or related machine learning and artificial intelligence data architectures.

The Role:

We’re looking for a Data Architect to drive the design, evolution, and governance of data architecture across the organization. In this role, you’ll collaborate closely with multiple functional groups and technology leaders to translate business needs into scalable, well-structured data solutions.

You’ll provide best-practice guidance on data management, modeling, and architecture design, ensuring data platforms are robust, efficient, and aligned with strategic objectives.

This is an exciting opportunity to shape data-centric initiatives, influence enterprise-level decisions, and enable teams to leverage high-quality data in support of impactful business outcomes.

The main responsibilities of the position include:

Develop conceptual, logical, and physical data models, focusing on design (structure, semantics, constraints, and alignment to business meaning), including key physical design considerations such as indexing and partitioning
Define and maintain reference and target data architectures (including standards and reusable patterns) across operational systems, event/streaming platforms, and analytical environments (data warehouse/lakehouse)
Drive architectural decision-making and trade-offs (e.g., consistency, performance, scalability, cost, operability, security), and contribute to architecture documentation practices that capture and govern those decisions
Support the implementation of the organizational data strategy, including database design standards, data warehouse architecture, standards and guidance, and analytics platform integration
Assist with the deployment and extension of the Enterprise Data Catalogue
Contribute to the creation and maintenance of architecture processes and documentation standards
Partner closely with project teams as an embedded contributor, guiding schema design, physical design choices (e.g., indexing and partitioning), data access patterns, and query optimization best practices, supporting teams through design reviews and delivery
Advise project teams on the end-to-end data product lifecycle, from platform selection through testing and implementation
Govern changes to architectural artefacts and ensure systems conform to established data architecture guidelines
Define data flows and integration patterns across applications and services, including operational systems, streams, and analytical platforms (batch and real-time), with clear ownership and information dissemination patterns

Main requirements:

BSc/MSc in Computer Science, Information Technology or related field.
Minimum of 3 years of experience in data modelling, data engineering, database design, or data architecture roles.
Strong expertise in conceptual, logical, and physical data modelling, with solid SQL skills to bring designs to life.
Proficiency in Python for data-related work (e.g., automation, prototyping, analysis, validation, data quality checks, and tooling around data pipelines/integrations).
Experience working with cloud-based data platforms and modern data warehouse or lakehouse architectures
Good understanding of software development lifecycles, requirements analysis, and technical design best practices.
A collaborative mindset, with the ability to build trusted relationships across business and technical teams.
Exposure to data governance, metadata management, and data quality frameworks, with an appreciation for well-managed data.
Confidence in advising on ETL/ELT patterns, data integration solutions, and data orchestration technologies.
Experience in graph databases, vector databases/semantic search capabilities, feature stores, or related ML/AI data architectures would be considered a plus.
A proactive, self-driven professional who thrives in agile environments and enjoys shaping scalable data solutions.

Benefit from:

Attractive remuneration package
Private health insurance
Corporate pension fund
Intellectually stimulating work environment
Continuous personal development and international training opportunities

The Hiring Experience: What Awaits You

Let’s Connect – Intro Chat with Talent Acquisition 
Deep Dive – First Interview with Your Future Team 
Bring It to Life – Role-Specific Take-Home Task 
Final Connection – Final Interview

All applications will be treated with strict confidentiality!

By submitting this application, I confirm that I have read and agree to the terms of the Privacy and Data Protection Notice and the Confidentiality Undertaking.

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