Data Integration Architect

Job title: Data Integration Architect

Will the role be 100% remote, hybrid or 100% office? Hybrid 2-3 days/week

If the role is hybrid/ office based specify location: London/Coventry, UK

Duration of assignment: 6-12 Months contract InsideIR35

`

The Role

This role plays a key part in shaping and delivering an enterprise scale data observability and reconciliation framework within a major UK based organization undergoing digital and data led transformation. You will design integration and data architectures that compare and validate data across legacy and strategic platforms, ensuring critical business data remains accurate, consistent and trustworthy. The position provides exposure to modern cloud data platforms, streaming and event driven integration, monitoring and observability tooling, and configuration driven frameworks, while working on high impact, mission critical initiatives that directly enhance decision making and customer outcomes.

Key responsibilities:

Own the end to end integration and data architecture for cross system data comparison, data quality and reconciliation frameworks.

Design configuration driven, reusable patterns that enable multiple systems and domains to plug into a common observability and reconciliation platform.

Define batch, streaming and API based integration patterns to ingest and synchronise data across heterogeneous systems and cloud data platforms.

Specify data models and layering (landing, operational, reporting) to support large scale, auditable comparison and data quality use cases.

Architect how discrepancies, exceptions and metrics are captured, classified and exposed to downstream consumers and monitoring tools.

Define metrics, alerts and dashboard requirements with observability teams to monitor reconciliation health and data quality trends.

Translate enterprise architecture and data governance principles into practical standards, guardrails and reference designs for delivery teams.

Produce clear high level and low level designs, including assumptions, risks and decisions, to guide data and integration engineering teams.

Collaborate with architects, engineers and product stakeholders to align technical direction with business priorities and non functional requirements.

Provide technical leadership and review for new use cases to ensure consistent adoption and evolution of the integration and observability framework.

Key skills/knowledge/experience:

Strong experience as an Integration Architect or Data Integration Architect in complex, multi system enterprise environments.

Proven track record designing hybrid integration architectures spanning batch, streaming and API based integrations.

Solid understanding of cloud data platforms and data warehousing concepts, with strong SQL and data modelling skills.

Experience designing configuration driven or metadata driven frameworks for data quality, reconciliation or cross system comparison.

Good knowledge of enterprise integration patterns, including messaging, events, file based interfaces and microservice integration.

Exposure to data quality and observability concepts such as validation rules, anomaly detection, metrics and lineage.

Experience integrating data and integration platforms with monitoring/observability tools to drive dashboards and alerts.

Demonstrated ability to translate conceptual architecture and principles into clear, implementable designs and standards.

Strong communication, documentation and stakeholder management skills across technical and non technical audiences.

Experience working with cross functional teams in large transformation or modernisation programmes.

Desirable skills/knowledge/experience:

Experience designing or implementing enterprise data reconciliation or “system to system comparison” solutions in data critical environments.

Familiarity with at least one major public cloud platform (AWS, Azure or GCP) and associated data/integration services.

Hands on exposure to modern data quality, data observability or monitoring tools and their integration patterns.

Experience in industries where data accuracy and consistency are business critical (e.g. retail, financial services, utilities, telecoms).

Knowledge of data governance frameworks or practices (e.g. stewardship, data ownership, data quality management).

Understanding of CI/CD practices for data and integration assets, including versioning of schemas, pipelines and configuration.

Experience leading or influencing multiple delivery teams to adopt shared integration and data architecture standards.

Background in solution or technical design roles before progressing into integration architecture.