Engineering Manager - Data & AI

About Us 

As a leading group of companies, the ECA International Group stands as a global frontrunner in simplifying international mobility. Our collective vision is to make a positive impact by delivering exceptional products and services to our prestigious list of large enterprise clients. 

Our global presence across the UK, EU, Hong Kong, Australia, and the US offers our team a world of opportunities, and our commitment to innovation ensures that you will be at the leading edge of your field. 

We love to invest in our people’s success and development pathways, creating a diverse and inclusive community where your unique talents shine. Your work here has a global impact, and we prioritise work-life balance, offering flexibility to enable you to perform your best. Join us to experience a rewarding career where your potential is celebrated, and your journey to excellence begins. 

About the Job

This role is ideal for someone who wants to shape how a modern enterprise becomes truly AI-native. We already use AI in delivery and engineering, and we have strong guardrails and governance in place. Now, we’re looking for a leader who can help us scale: across data acquisition, ingestion, storage, and AI-powered consumption within a secure, multi-tenant environment.

You’ll evolve our existing data platform (AWS, Snowflake, S3, Postgres, event-driven services) into a product-facing, AI-ready foundation, while partnering across disciplines and leading a team in a supportive, high-trust environment.

If you're passionate about data, excited about AI, and motivated by meaningful impact, this role gives you the autonomy, influence, and visibility to shape how AI is adopted across the company.

Key Responsibilities

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.

2.        Data acquisition & ingestion

• 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.

3.        AI as a consumption layer

• 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.

4.        Partnering with Analytics

• Give the research teams clean, modelled, well-documented data.
• Turn one-off work into scheduled, production jobs.

5.        Guardrails, governance, and quality

• Keep AI-generated code within SDLC, code review, and security bounds.
• Ensure data and AI services are audited and tenant aware.

6.        Team leadership

• 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.

7.        Delivery & Accountability

• 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

8.        Technical Direction & Architecture

• 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

9.        Agile & Product Collaboration

• 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

10.  Quality & Continuous Improvement

• 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

The Ideal Candidate:

1. Data-first mindset

You understand how data arrives in an organisation: via APIs, files, partner feeds, human/crowd sourced inputs or from the internet and that each of those has different latency, quality, and governance needs.

You’re comfortable with:

• 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,

2. AI-positive, not AI-sceptic
This role is for someone who:

• 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.

3. Enterprise-aware
We have clients, tenants, and compliance, so you will:

• 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.

4. Builder + Manager
You’re happy to open the IDE and build the pipeline, but you can also run a small team, set standards, review code, and coach people into AI-native ways of working.

What’s in it for you

• 💼 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

We are a super friendly team that thrives on collaboration and supporting each other. We cultivate an environment where everyone feels valued and empowered to contribute their best work, helping us to realise our ambitious growth goals and mission. We live our Values of Integrity, Respect, Ambition and Innovation and this shows up loud and proud in everything we do. Our hybrid working structure includes spending around two days a week at our Head Office in Holborn, London.