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For Companies At a Glance
- Tasks: Lead data engineering initiatives and design scalable data solutions.
- Company: Major financial services organisation investing in next-gen data and AI.
- Benefits: Competitive salary, strong benefits, and hybrid working model.
- Why this job: Join a dynamic team and influence cutting-edge data and AI capabilities.
- Qualifications: Experience leading data engineering teams and expertise in cloud platforms.
- Other info: Opportunity for career growth in a rapidly modernising environment.
The predicted salary is between 43200 - 72000 £ per year.
Overview
Associate Director – Data & AI Recruitment
Location: South England x2 days a month in office. Package: Competitive salary + strong benefits.
We’re representing a major financial services organisation that is investing heavily in next-generation data and digital platforms. They are building a modern, cloud-native data ecosystem to power AI, analytics, and customer-facing innovation and now seek a Lead Data Engineer to guide this transformation. The company has an incredible Data Leadership team with good tenure, and alongside impactful Data Science projects, they have multiple AI / LLM based projects in production due to their mature Data offering. This is a rare opportunity to join the team at an impactful, senior level due to the typically very long tenure.
The role
This position blends technical leadership with hands-on engineering. You’ll oversee the design and delivery of scalable data solutions, lead and mentor a small engineering group, and set the standards for how data is built, managed, and consumed across the organisation.
It’s a chance to make architectural decisions, work directly with product and AI specialists, and drive forward best practices in a rapidly modernising environment.
Key responsibilities
- Directing major data engineering initiatives and overseeing a team of engineers
- Designing and enhancing data warehouses, pipelines, and integration frameworks at scale
- Partnering with analytics, AI, product, and business teams to create end-to-end data solutions
- Defining coding guidelines, frameworks, and operating models across the platform
- Leading the migration of legacy environments into a flexible, cloud-first stack
- Contributing to the build and delivery of advanced data products and GenAI-enabled applications
- Raising the bar on data quality, governance, and compliance processes
Skills & experience required
- Proven background leading data engineering teams or projects in a technology-driven business
- Expert knowledge of modern cloud data platforms (Databricks, Snowflake, ideally AWS)
- Advanced Python programming skills and fluency with the wider Python data toolkit
- Strong capability with SQL, Spark, Airflow, Terraform, and workflow orchestration tools
- Solid understanding of CICD practices using Git, Jenkins, or equivalent tooling
- Hands-on experience building both batch and streaming data integration pipelines
- Depth in data modelling, ingestion, and optimisation for large-scale environments
- Any exposure to production use of Generative AI is highly advantageous
What’s on offer
- A hybrid working approach that values flexibility
- The opportunity to combine leadership responsibilities with technical delivery
- Influence over the design of next-generation data and AI capabilities within a household-name financial services brand
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Lead Data Engineer employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Network like a pro! Reach out to connections in the industry, attend meetups, and engage on platforms like LinkedIn. We can’t stress enough how personal connections can lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Prepare for those interviews! Research the company’s data initiatives and be ready to discuss how your experience aligns with their goals. We recommend practising common interview questions and even some technical challenges related to data engineering.
✨Tip Number 3
Showcase your projects! Whether it’s through a portfolio or GitHub, let your work speak for itself. We believe that demonstrating your hands-on experience with cloud data platforms and AI projects can really set you apart from the competition.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. We’re here to help you land that Lead Data Engineer role, so don’t hesitate to take that step!
We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your leadership in data engineering and any relevant projects you've worked on, especially those involving cloud platforms like AWS or Databricks.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for the Lead Data Engineer role. Share specific examples of how you've led teams and delivered scalable data solutions, and don’t forget to mention your passion for AI and analytics!
Showcase Your Technical Skills: In your application, be sure to emphasise your technical expertise, particularly in Python, SQL, and data integration tools. We want to see how you’ve applied these skills in real-world scenarios, so don’t hold back on the details!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Xcede
✨Know Your Tech Inside Out
Make sure you’re well-versed in the modern cloud data platforms mentioned in the job description, like Databricks and Snowflake. Brush up on your Python skills and be ready to discuss how you've used SQL, Spark, and Airflow in past projects.
✨Showcase Your Leadership Skills
Since this role involves leading a team, prepare examples of how you've successfully managed engineering teams or projects. Think about specific challenges you faced and how you guided your team through them.
✨Understand the Business Context
Familiarise yourself with the financial services sector and how data plays a role in driving innovation. Be prepared to discuss how your technical decisions can impact business outcomes and customer experiences.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data engineering. Practice articulating your thought process when designing scalable data solutions or migrating legacy systems to a cloud-first stack.
