Data Architect in Romford

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Contract Type: Fixed-Term Contract

Industry: Utilities / Regulated Environment (experience preferred)

Role Summary

We are looking for a highly capable Data Architect who can translate business needs into robust data architectures, lead end-to-end design across multiple technology landscapes, and ensure data integrity, governance, and quality throughout our data estate. This role requires someone who can work confidently with business stakeholders, solution architects, data engineers, and product teams to shape, govern and deliver data-driven solutions that support operational, analytical, and regulatory objectives.

You will play a pivotal role in designing conceptual, logical, and physical data models; embedding data quality and governance into our pipelines; and ensuring our data products are scalable, reliable and aligned to our enterprise architecture and strategy.

This is an excellent opportunity for an architect with depth in both data modelling and data governance—and the ability to lead design, steer delivery, and manage stakeholder nuance in a complex, multi-domain technology landscape.

Key Responsibilities

• Develop conceptual, logical, and physical data models for operational, analytical, and regulatory workloads.
• Create and maintain data architecture blueprints and reference architectures covering ingestion, integration, storage, lineage, and consumption.
• Define modelling patterns (3NF, dimensional/star, Data Vault, canonical models) and guide teams on when and how to apply them.
• Optimise physical designs for performance, scalability, cost and resilience across cloud data platforms (e.g., Snowflake, Databricks, Synapse, BigQuery).
• Lead design reviews, ensuring models are accurate, high-quality, and aligned with business capabilities and domain boundaries.

Data Governance & Metadata Management

• Define data ownership, stewardship models, and contribute to the governance operating framework.
• Build and maintain data dictionaries, business glossaries, critical data elements (CDEs) and metadata standards.
• Ensure all data solutions align with governance policies, including lineage, retention, access, and security requirements.
• Support governance forums and collaborate with business stewards to drive consistent definitions and controlled change.

Data Quality Architecture & Pipelines

• Embed data quality rules and dimensions (completeness, timeliness, accuracy, uniqueness, validity, consistency) across ETL/ELT and streaming pipelines.
• Design data quality metrics, alerts, and monitoring frameworks to surface quality issues to stewards and downstream consumers.
• Partner with engineering teams to implement automated DQ checks, profiling, and remediation patterns.
• Ensure DQ scoring and lineage are built into architecture in a systematic and reusable way.

Stakeholder Engagement & Requirements Leadership

• Lead architectural discovery to capture business needs, translate them into data requirements, and shape programme/solution scope.
• Manage and communicate architectural decisions with senior business and technical stakeholders.
• Navigate ambiguity and stakeholder nuance, ensuring alignment across product teams, SMEs, vendors, and governance bodies.
• Produce high-quality design documentation and present designs to Architecture Review Boards or equivalent governance forums.

Delivery Governance & Technical Leadership

• Oversee the implementation of data architectures and ensure engineering teams follow patterns, standards, and best practices.
• Provide technical guidance on integration design, ingestion patterns, transformation methods, caching, orchestration, and storage optimisation.
• Conduct design assurance throughout delivery, ensuring solutions adhere to non-functional requirements (performance, availability, resilience, cost).
• Coach engineers, analysts, and stewards on modelling, data quality, and governance practices.

Skills & Experience Required

• Proven experience as a Data Architect, Solution Architect with strong data background, or senior data engineer/analyst transitioning into architecture.
• Demonstrable expertise in conceptual, logical, and physical data modelling with clear understanding of modelling patterns and trade-offs.
• Strong understanding of data governance frameworks, metadata management, data ownership/stewardship models, and business glossaries.
• Hands‑on experience embedding data quality rules, profiling, scoring, and exception management into pipelines.
• Familiarity with modern cloud data platforms (Snowflake, Databricks, Azure Synapse, BigQuery, Redshift, etc.).
• Ability to lead architectural thinking across multiple domains and manage stakeholder complexity.
• Ability to produce high-quality architectural artefacts: blueprints, models, solution designs, integration specifications.
• Experience working in regulated sectors (utilities, financial services, health, etc.) is advantageous.
• Experience with data mesh, domain‑driven design, or federated data ownership models.
• Experience with Great Expectations, dbt tests, or enterprise DQ tooling.
• Knowledge of MDM, reference data management, and semantic modelling.
• Experience with streaming platforms (Kafka, EventHub) and API‑based integration.
• Understanding of AI/ML data preparation pipelines and feature store design.

What Success Looks Like in This Role

• Clear, scalable data models adopted across teams and projects.
• High trust and alignment among stakeholders because architectural decisions are well‑reasoned and clearly communicated.
• Measurable improvements in data quality, lineage visibility, and governance adoption.
• Production of repeatable design patterns and frameworks that accelerate delivery.
• Delivery teams are confident, aligned, and able to execute effectively because the architecture removes ambiguity.

Why Join Us?

• Work at the centre of a major transformation in a sector where reliable data is mission‑critical.
• Influence enterprise‑level data strategy and shape how data is governed, modelled, and used across the organisation.
• Join a team that values architectural thinking, collaboration, transparency, and continuous learning.
• Opportunity to work across diverse data domains including asset management, customer operations, leakage, regulatory reporting, and sustainability.

Seniority level

• Mid‑Senior level

Employment type

• Full‑time

Job function

• Engineering and Information Technology

Industries

• Utilities