Engineering Manager - Data & AI

ECA International Ltd; City of Westminster; Hybrid; GBP 70,000 - 85,000; Full time

Job summary

A global leader in international mobility is looking for an experienced technical lead to oversee AI-native data solutions. The role involves guiding a small technical team, ensuring high-quality delivery of data services, and translating AI concepts into practical applications. Ideal candidates will have deep expertise in AWS, Snowflake, and a strong understanding of data governance, while fostering a collaborative environment. Flexible working options are available, along with a range of employee benefits.

Benefits

Enhanced Stakeholder Pension Contribution

25 days annual leave

Health, Life Insurance + EAP Wellbeing Support

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

Qualifications

• Understanding data ingestion from various sources: APIs, files, etc.
• Comfortable with AI concepts and translating them into secure services.
• Ability to design with security and compliance in mind.

Responsibilities

• Take accountability for high-quality software delivery.
• Drive planning and execution measuring impact by business outcomes.
• Lead a small technical team and promote AI-native practices.

Skills

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 data pipeline management

AI enthusiasm

Understanding of security and governance in AI

Ability to mentor and lead a technical team

Job description

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 for Architecting 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.

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 is an exciting role for someone who wants to help shape a real transition to an AI‑native company. We are already using AI in delivery and AI tools for software development including code generation, and we have guardrails and governance in place. Your job is to make that scale across data acquisition, ingestion, storage, and AI‑powered consumption inside an enterprise, multi‑tenant environment. You will take an existing data platform (AWS, Snowflake, S3, Postgres, event‑driven services) and make it product‑facing and AI‑ready focusing on new Data Production delivery and Data Insights experiences.

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