Lead-Data Automation and Excellence

Solution Architecture & Technical Enablement

• Drive solution architecture for data across ingestion, curation, and consumption layers.
• Guide squad members in problem-solving complex technical challenges and support implementation of sound, scalable solutions.
• Shape technology standards and framework to ensure adherence to coding standards, architectural patterns, and data engineering best practices.
• Mentor and coach engineers to raise overall technical maturity and delivery quality within the squad.
• Lead the technical design of data assets using a medallion architecture (Bronze, Silver, Gold) working with the Technical Product owners within a federated data product squad model.
• Recommend and introduce improved technical approaches to data architecture, modelling tools, and solution design to enhance scalability and maintainability.
• Drive technical improvements in data curation practices using Change Data Capture (CDC) and event-driven curation patterns.
• Design and guide implementation of event-driven and streaming architectures, including Kafka-based solutions integrated with batch pipelines.

Operational Excellence & SDLC

• Improve operational efficiency through optimization of CI/CD pipelines aligned with the enterprise SDLC toolchain.
• Promote automation working in partnership with information architects by introducing tools and AI driven capabilities across testing, deployment, data quality validation, and observability to reduce manual effort and operational support risk.
• Actively manage and prevent accumulation of technical debt while balancing delivery commitments.

AI Enablement & Data Readiness

• Apply data engineering best practices alongside strong AI and GenAI literacy, including:
• Prompt engineering and AI-assisted development
• Large Language Models (LLMs) and GenAI concepts
• Data profiling and automated asset creation

Other Duties

• Partner with Product Owners to refine technical requirements, define acceptance criteria, and support backlog shaping.
• Collaborate with other Lead Engineers to align on standards, manage cross-squad dependencies, and resolve shared technical challenges.
• Stay current with emerging data engineering, streaming, and AI technologies and assess their applicability within the platform ecosystem.
• Support onboarding of new engineers by providing guidance on tools, frameworks, and engineering practices.