The Modern Data Platform (MDP) Architect / Consultant / Developer designs, builds and operates enterprise-grade data and analytics platforms using modern, cloud-native and platform-agnostic architecture patterns, implemented on data platforms. The role enables organisations to deliver trusted data, analytics, business intelligence (BI) and artificial intelligence/machine learning (AI/ML) use cases in a scalable, secure and cost-effective manner.

Depending on experience and seniority, the role may focus on hands-on platform development and delivery (Developer / Consultant) or on end-to-end data platform architecture, standards and data strategy (Architect). The role collaborates closely with business stakeholders, data teams, cloud architects and security teams to ensure the platform is future-proof, governed and enterprise-ready.

Key Responsibilities

Data platform design and delivery (platform-agnostic)

Design and deliver modern data platforms using cloud-agnostic patterns (data lakes, lakehouses and data warehouses), supporting batch, streaming and near real-time processing.
Build data ingestion, transformation and analytics pipelines, and enable data consumption for reporting, analytics and downstream applications.
Support integration across cloud platforms and data technologies, aligning to client architecture, security and operating model requirements.

Architecture and platform standards (Architect focus)

Define Modern Data Platform reference architectures and standards independent of vendor or cloud (including ingestion, modelling, governance, security and access).
Design scalable, resilient and cost-optimised architectures and provide architectural oversight across delivery teams.

Data Engineering, Analytics & AI Enablement

Develop and optimise data pipelines and transformations.
Design analytical and reporting data models.
Implement data quality, metadata, and lineage practices.
Support advanced analytics and AI/ML enablement where required.

Operations, Governance & Optimisation

Define monitoring, performance tuning, and cost management practices.
Ensure data security, privacy, and compliance controls are applied.
Support platform lifecycle management, CI/CD, and environment strategy.
Contribute to platform documentation, standards, and operational runbooks.

Collaboration & Advisory

Collaborate with business users, analysts, data scientists, and IT teams.
Advise stakeholders on technology choices and architectural trade-offs.
Mentor junior developers and consultants (Senior / Architect level).

Skills, Experience and Competencies

Technical Skills

Strong understanding of modern data architectures (data lake, lakehouse and data warehouse), and experience integrating across cloud services and data ecosystems.
Strong SQL, data modelling, and analytical design skills.
Exposure to streaming, real-time, or event-driven data processing.
Understanding of data governance, security, and cost optimisation.

Experience (Role Level Determination)

MDP Architect

10–15+ years of data and analytics experience.
7–10+ years designing enterprise scale data platforms.
Proven experience defining platform agnostic data strategies and architectures.

Competencies

Data product mindset, treating datasets, semantic models and reporting outputs as products with clear owners, consumers, quality measures and lifecycle management.
Business-to-technical translation and collaboration, working with stakeholders and delivery teams to shape use cases and requirements, and translating them into practical Fabric design decisions and incremental delivery plans.
Trusted data and quality by design building pipelines and models with validation, testing, lineage and reconciliation so teams can rely on data for analytics and AI-ready use cases.
Standardise use shared patterns, templates, reference designs and accelerators to improve speed, quality and consistency across delivery.
Iterative, outcome-driven delivery executing value in increments (ingestion → lake / lakehouse / warehouse → semantic model → reports), validates with users, and applies reusable patterns and automation to improve consistency.

Qualifications and Certifications

Cloud data or analytics certifications (Azure, AWS, GCP).
Platform specific certifications (Fabric, Databricks, Snowflake – desirable, Informatica- desirable).
Architecture certifications (Architect level – desirable).

If this opportunity interests you and you are open to exploring new roles, I'd be happy to discuss it further. You may share your updated CV here or send it to [HIDDEN TEXT].

Modern Data Platform Architect