1. Data platform evolution

Take our current AWS/Snowflake/S3/Postgres setup and enable AI/RAG, product consumption, and multi-tenant access.
Work with the Technical Architect to keep this aligned with our event-driven and security model.
Design multi-source ingestion (APIs, scraping/crawling, file drops, crowdsourcing, agent-based pipelines).
Make it observable, repeatable, and documented so research and analytics can plug in new sources without rework.
Build LLM/RAG endpoints on top of our data and content as a service.
Expose these services to Data Insights to enable users to ask, explore, and generate insights - not only download reports.
Give the research teams clean, modelled, well-documented data.
Turn one-off work into scheduled, production jobs.
Keep AI-generated code within SDLC, code review, and security bounds.
Ensure data and AI services are audited and tenant aware.
Lead a small technical team (data/AI/ingestion).
Promote AI-native ways of working across product, data, and engineering.
Manage and mentor your engineering team, fostering a collaborative, high-performance environment with excellent productivity.
Demonstrate hands-on technical excellence while modelling accountability, critical thinking, and AI-first practices
Set clear objectives, provide regular feedback, conduct performance reviews.
Take full accountability for the delivery of high-quality software products, owning both successes and challenges
Drive outcome focused delivery planning and execution, measuring success by business impact rather than effort or hours invested
Proactively identify and mitigate risks, making critical decisions to keep projects on track
Guide technical direction, establish best practices, and ensure architectural decisions support scalability, maintainability, and business goals
Be a hands-on contributor forArchitecting and building well-tested, maintainable applications
Optimise tech stacks and development workflows to maximise team productivity
Ensure Agile ceremonies (sprint planning, retrospectives, stand-ups) are followed and continuously refine Agile practices to optimise team performance
Collaborate with product owners and stakeholders to develop and maintain technical roadmaps that align with business strategy
Work with product owners to build and maintain a prioritised backlog that balances business value, technical debt, and innovation
Enforce rigorous quality standards including test-driven development (TDD), code reviews, and automated testing
Ensure that security best practices are followed to the highest standards
Foster a culture of experimentation, learning, and continuous improvement
Use data and metrics to drive decisions and demonstrate improvement in team velocity, quality, and business outcomes
AWS (core services, IAM basics, networking good practice),
Snowflake (or similar cloud data warehouse),
Amazon S3 for landing/staging data
Postgres (including JSONB/dynamic fields),
Event-driven patterns for efficient and effective data pipeline management,
is genuinely enthusiastic about AI/LLMs/agents,
is actively learning (even in their own time),
Can translate AI concepts (RAG, agents, tools, function calling, model evaluation, private models) into working, secure services.
design with security, PII and tenancy in mind,
accept governance and SDLC gates as part of making AI safe,
and still find a way to deliver fast.

Enhanced Stakeholder Pension Contribution
25 days annual leave
Health, Life Insurance + EAP Wellbeing Support
Eligible for Annual Bonus Scheme
Long Service Awards
️ ️ ClassPass Membership
Enhanced Family Leave
Up to £1,000 per year for personal development & training
Season Ticket Loan
Flexible/hybrid Work Environment
Cycle to Work Scheme
Free Eye Test

1 Eca International Ltd jobs in England & Wales