Senior Data Architect

Jobtailor; Greater London; On-site; GBP 110,000 - 150,000; Full time

Job summary

Jobtailor is seeking an Enterprise Data Architect to modernise the data platform and drive operational excellence through automation.

You will design cloud-based data solutions, define lakehouse models, and embed DevOps, governance, and security into real-time pipelines. Lead AI solution architecture and guide workshops aligning with TOGAF principles.

Qualifications

• Proven experience architecting enterprise-scale data solutions including lakehouse concepts and real-time pipelines.
• TOGAF Certification is required.
• Track record of optimising cost, performance and outcomes under strict compliance.
• Advanced knowledge of Java/Spring, Python, Docker, Kubernetes, AWS and DevOps methodologies.
• Familiarity with Spark, Iceberg, Parquet and large-scale data processing.
• Experience with ML and analytics, including LLMOps and MLOps practices.
• Pipeline automation and model governance experience.
• Ability to lead AI solution architecture rather than day-to-day model development.
• Skills in defining and enforcing data governance standards.
• Knowledge of regulatory and information security best practices and navigating regulated environments.
• Workshop facilitation and bridging technical and non-technical perspectives.
• Self-driven approach and passion for continuous improvement.

Responsibilities

• Design cloud-based data solutions meeting functional and non-functional requirements.
• Define conceptual and logical models for data lakes, warehouses, and hybrid AWS/Azure deployments.
• Embed DevOps practices, automation, monitoring, security, and regulatory compliance.
• Orchestrate large-scale data pipelines using Spark, Docker, Kubernetes, and DevOps tools.
• Apply standardised processes and automated testing to accelerate delivery while handling terabytes of data daily.
• Set the architectural framework for building, training, and deploying AI/ML models through LLMOps and MLOps.
• Oversee model improvement, versioning, monitoring, real-time personalization, and analytics workflows.
• Define schema management, metadata, and data quality controls with the Data Governance Manager.
• Integrate information security standards and compliance into data processes.
• Lead whiteboard sessions, technical workshops, and design reviews.
• Translate complex architecture concepts into actionable strategies aligned with TOGAF principles.
• Track emerging cloud, DevOps, and AI technologies and evaluate innovations such as vector databases and real-time analytics.

Skills

TOGAF Certification

Enterprise Architecture

Cloud AWS

DevOps

Java

Python

Docker

Kubernetes

Spark

LLMOps

MLOps

Data Governance

Information Security

Regulatory Compliance

Workshop Facilitation

Technical Communication

Cost & Performance Optimisation

Tools

Docker

Kubernetes

Job description

• Modernise the A&I data platform architecture and drive operational excellence through automation
• Design cloud-based data solutions meeting functional and non-functional requirements
• Define conceptual and logical models for data lakes, warehouses, and hybrid AWS/Azure-Fabric deployments
• Embed DevOps practices, automation, monitoring, security, and regulatory compliance
• Orchestrate large-scale data pipelines using Spark, Docker, Kubernetes, and DevOps tools
• Apply standardised processes and automated testing to accelerate delivery while managing terabytes of data daily
• Set the architectural framework for building, training, and deploying AI/ML models through LLMOps and MLOps
• Oversee model improvement, versioning, monitoring, real-time personalisation, and advanced analytics workflows
• Define schema management, metadata frameworks, and data quality controls with the Data Governance Manager
• Integrate information security standards and compliance requirements into data processes
• Lead whiteboard sessions, technical workshops, and design reviews
• Translate complex architecture concepts into actionable strategies and align with Enterprise Architecture and TOGAF principles
• Track emerging cloud, DevOps, and AI technologies and evaluate innovations such as vector databases and real-time analytics

Requirements

• Proven experience architecting enterprise-scale data solutions, including lakehouse concepts, big data platforms, and real-time pipelines
• TOGAF certification
• Track record of optimising cost, performance, and business outcomes under strict compliance requirements
• Advanced knowledge of Java/Spring, Python, Docker, Kubernetes, AWS, and DevOps methodologies
• Familiarity with Spark, Iceberg, Parquet, and large-scale data processing solutions
• Competence in ML and analytics, with exposure to LLMOps and MLOps practices
• Experience with pipeline automation and model governance
• Ability to lead AI solution architecture rather than day-to-day model development
• Skills in defining and enforcing data governance standards
• Knowledge of regulatory and information security best practices
• Ability to navigate a highly regulated environment
• Workshop facilitation and ability to bridge technical and non-technical perspectives
• Self-driven approach and passion for continuous improvement, developer productivity, and accelerating time-to-market

Core Competencies

Demonstrates expertise in architecting enterprise-scale data solutions, including lakehouse concepts and real-time data pipelines, while ensuring compliance with regulatory standards. Proficient in leading AI solution architecture and implementing data governance frameworks to optimize performance and business outcomes.

Highest-signal resume keywords

• TOGAF Certification
• AWS Cloud Solutions
• DevOps Methodologies
• Data Governance Standards
• AI/ML Solution Architecture

ATS Optimization Keywords

Hard Skills

• Java
• Spring
• Python
• Docker
• Kubernetes
• Spark
• Iceberg
• Parquet
• MLOps
• LLMOps

Soft Skills

• Workshop Facilitation
• Technical Communication
• Self-Driven Approach

Certifications & Qualifications

• TOGAF Certification

Industry Keywords

• Data Governance
• Information Security
• Regulatory Compliance
• Operational Excellence
• Data Quality Controls

Tools & Technologies

• Data Lakes
• Data Warehouses
• Big Data Platforms
• Real-Time Analytics
• Automation Tools