A&I - Senior Data Architect

About the role

As a Senior Data Architect at Kindred Group, you will be responsible for designing advanced data architectures and modernizing data pipelines. Your work will involve defining models for data lakes and warehouses, embedding automation, and ensuring compliance with security and regulatory standards.

You will collaborate closely with cross-functional teams, leading technical workshops and influencing stakeholders to translate complex architectural concepts into actionable strategies. Success in this role means enhancing operational efficiency while maintaining high standards of data governance and quality.

Skills that matter here

• Java: This role requires advanced knowledge of Java for architecting data solutions.
• Python: Python skills are needed for implementing scalable data frameworks.
• Docker: Docker will be used to orchestrate large-scale data pipelines.
• Kubernetes: Kubernetes is essential for managing containerized applications in data workflows.
• AWS: Experience with AWS is critical for defining cloud-based data architectures.
• Spark: Familiarity with Spark is necessary for processing large datasets efficiently.

Who this role suits

• Experienced data architects with a proven track record in enterprise-scale data solutions.
• Individuals who thrive in a collaborative environment and enjoy leading technical discussions.
• Candidates who are self-driven and passionate about continuous improvement and innovation.
• Professionals comfortable navigating regulatory landscapes while advocating for best practices in data governance.

From the employer

What You’ll Be Doing

• Architecting Advanced Data Solutions: Shape End-to-End Data Architectures
• Define conceptual and logical models for data lakes, warehouses, and hybrid deployments (AWS, Azure/Fabric), aligning with key performance and cost objectives.
• Embed Automation & Monitoring: Reduce complexity and maximise uptime through DevOps practices, ensuring compliance with FDJ United’s security and regulatory standards.
• Modernising Data Pipelines & Workflows: Implement Scalable Frameworks
• Orchestrate large-scale pipelines using Spark, Docker, Kubernetes, and other DevOps tools.
• Accelerate Delivery: Apply standardised processes and automated testing to streamline development and reduce time-to-market while managing terabytes of data daily.
• Driving AI & ML Initiatives: Champion LLMOps & MLOps Strategy
• Set the architectural framework for building, training, and deploying AI/ML models with automation and regulatory compliance in mind.
• Enhance Operational Efficiency: Oversee end-to-end workflows (model improvement, versioning, monitoring) to support real-time personalisation and advanced analytics, focusing on architectural integrity rather than hands-on coding.
• Ensuring Governance & Quality: Establish Strong Data Governance
• Partner with the Data Governance Manager to define schema management, metadata frameworks (e.g., OpenMetadata), and data quality controls, promoting data democratisation and self-service.
• Adhere to Security & Compliance: Integrate information security standards and FDJ United’s compliance framework into every data process, safeguarding internal and customer data across all stages.
• Collaborative Design & Leadership: Lead Technical Workshops
• Host whiteboard sessions and design reviews, driving shared expertise and open dialogue.
• Influence Stakeholders: Translate complex architectural concepts into actionable strategies, aligning with the PAM Enterprise Architect team and TOGAF principles.
• Continuous Innovation & Exploration: Stay Ahead of Trends
• Track emerging data technologies in cloud, DevOps, and AI to maintain a cutting-edge platform.
• Evaluate & Implement New Solutions: Prototype and integrate innovations—such as vector databases or advanced real-time analytics—that bring tangible business impact.

What We’re Looking For

• Deep Data Architecture Expertise: Proven experience architecting data solutions at enterprise scale (lakehouse concepts, big data platforms, real-time pipelines).
• TOGAF Certified: Successful track record of optimising cost, performance, and business outcomes under strict compliance requirements.
• Technical Mastery & Hands-On Skills: Advanced knowledge of Java/Spring, Python, Docker, Kubernetes, AWS and DevOps methodologies.
• Familiarity with Spark, Iceberg, Parquet, and other solutions for large-scale data processing.
• AI/ML & Analytics Background: Competent in ML & analytics, with exposure to LLMOps and MLOps practices (pipeline automation, model governance).
• Comfortable leading the architecture of AI solutions rather than day-to-day model development.
• Governance, Security & Compliance Mindset: Skilled in defining and enforcing data governance standards while upholding regulatory and information security best practices.
• Ability to navigate a tough regulatory landscape, ensuring compliance without compromising innovation.
• Excellent Communication & Collaboration: Adept at workshop facilitation and bridging technical and non-technical perspectives.
• Self-driven, with a passion for continuous improvement, developer productivity, and accelerating time-to-market.