At a Glance
- Tasks: Lead a team to evolve our data platform and implement AI solutions.
- Company: Join ECA International Group, a global leader in international mobility.
- Benefits: Enjoy flexible work, health benefits, and personal development funding.
- Other info: Collaborative culture with excellent career growth opportunities.
- Why this job: Shape the future of AI in a supportive, innovative environment.
- Qualifications: Experience in data management and a passion for AI technologies.
The predicted salary is between 70000 - 90000 £ per year.
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 a world of opportunities, and our commitment to innovation ensures that you will be at the leading edge of your field. We invest in people's success and development pathways, creating a diverse and inclusive community where your unique talents shine. You will have a global impact and a work‐life balance, with flexibility to perform your best.
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.
Key Responsibilities
- Data platform evolution: Take our current AWS/Snowflake/S3/Postgres setup and enable AI/RAG, product consumption, and multi‐tenant access.
- 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.
- 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.
- Partnering with Analytics: Give the research teams clean, modelled, well‐documented data. Turn one‐off work into scheduled, production jobs.
- 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.
- 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.
- 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.
- 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. Optimize tech stacks and development workflows to maximize team productivity.
- Agile & product collaboration: Ensure Agile ceremonies (sprint planning, retrospectives, stand‐ups) are followed and continuously refine Agile practices to optimize 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.
- 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
- 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.
- 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.
- AI‐positive, not AI‐sceptic: This role is for someone who is genuinely enthusiastic about AI/LLMs/agents, actively learning (even in their own time), can translate AI concepts (RAG, agents, tools, function calling, model evaluation, private models) into working, secure services.
- Enterprise‐aware: 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.
- Builder + Manager: You are 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.
Benefits
- 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. Our hybrid working structure includes spending around two days a week at our Head Office in Holborn, London.
Engineering Manager - Data & AI in London employer: ECA International
ECA International is an exceptional employer, offering a dynamic work environment in London where innovation meets collaboration. With a strong focus on employee development and a culture that values technical expertise, you will have the opportunity to lead a talented team while working with cutting-edge technologies like AWS and Snowflake. The company promotes a healthy work-life balance and provides ample growth opportunities, making it an ideal place for those seeking meaningful and rewarding careers in AI and data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Manager - Data & AI in London
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for interviews by researching the company and its culture. Tailor your answers to show how you fit into their vision, especially around AI and data-driven solutions.
✨Tip Number 3
Showcase your skills with a portfolio or projects that highlight your experience in data platforms and AI. This gives you a chance to demonstrate your hands-on expertise.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed and you’re considered for exciting roles like Engineering Manager - Data & AI.
We think you need these skills to ace Engineering Manager - Data & AI in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Engineering Manager role. Highlight your experience with data platforms, AI, and team leadership. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for AI and data, and explain why you’re excited about this role at ECA International Group. Let us know how you can make a positive impact.
Showcase Your Achievements:Don’t just list your responsibilities; showcase your achievements! Use metrics to demonstrate how you’ve driven success in previous roles. We love seeing tangible results that reflect your capabilities.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at ECA International
✨Know Your Tech Stack
Familiarise yourself with the specific technologies mentioned in the job description, like AWS, Snowflake, and Postgres. Be ready to discuss how you've used these tools in past projects and how they can be leveraged for data acquisition and AI integration.
✨Show Your AI Enthusiasm
Demonstrate your passion for AI by discussing recent trends or projects you've worked on that involved AI technologies. Share your thoughts on how AI can enhance data platforms and improve business outcomes, showing that you're not just knowledgeable but genuinely excited about the field.
✨Prepare for Team Leadership Questions
Since this role involves leading a technical team, be prepared to discuss your leadership style. Think of examples where you've successfully managed a team, fostered collaboration, and promoted a culture of continuous improvement. Highlight how you set objectives and provide feedback.
✨Understand Agile Methodologies
Brush up on Agile practices, as the role requires optimising team performance through Agile ceremonies. Be ready to explain how you've implemented Agile in previous roles and how it can benefit project delivery and team dynamics in a tech environment.
