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Lead Data Engineer

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Lead Data Engineer
Employment Type: Permanent
Location: London - Hybrid (3 days in the office)
Salary: £95,000 - £110,000 + benefits & bonus
About the Client
Our client is a leading specialist insurance provider, recognised for its innovative approach to technology and data. Operating globally, they are investing heavily in their modern data platform, leveraging cloud technologies to deliver scalable, high-quality data solutions that support underwriting, analytics and business decision-making.
Role Overview
As a Lead Data Engineer, you'll play a key role in designing and evolving a modern cloud-based data platform built on Databricks and Azure. You'll lead the development of scalable data pipelines using Python and PySpark, enabling high-quality data to power underwriting, analytics and business-critical decision-making across the organisation.
Working closely with Product Owners, Architects and business stakeholders, you'll provide technical leadership throughout the full data lifecycle. Alongside remaining hands-on, you'll mentor a team of Data Engineers, champion engineering best practices and help shape the future of the organisation's cloud data platform.
Key Responsibilities:
- Lead and mentor a team of Data Engineers, supporting the successful delivery of data engineering projects from design through to production.
- Design, develop and optimise scalable data pipelines using Python, PySpark and Databricks.
- Build and maintain cloud-native data solutions across the Azure ecosystem, including Azure Functions and related services.
- Collaborate with Product Owners, Architects and business stakeholders to define technical solutions and deliver against business priorities.
- Drive engineering best practices through code reviews, mentoring and continuous improvement initiatives.
- Identify opportunities to improve platform performance, data quality, scalability and operational efficiency.
- Champion automation, testing, CI/CD and modern engineering practices across the data engineering function.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Requirements:
- Strong commercial experience building data engineering solutions using Python, PySpark and Databricks.
- Proven experience designing and optimising complex SQL queries and working with large-scale datasets.
- Strong experience across the Azure technology stack, including Azure Functions and cloud-native data services.
- Previous experience leading or mentoring Data Engineers within an Agile environment.
- Strong understanding of distributed data processing, modern data engineering practices and CI/CD.
- Experience building scalable, reliable and high-performing data platforms.
- Experience within Financial Services or Insurance is highly advantageous.


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Why Join:
- Opportunity to shape the future of a modern, cloud-native data platform built on Databricks and Azure.
- Hands-on leadership role combining technical delivery with engineering strategy.
- Work with modern technologies including Python, PySpark, Databricks and the wider Azure ecosystem.
- Collaborative engineering culture focused on innovation, quality and continuous improvement.
- Competitive salary, bonus and comprehensive benefits package.
- Hybrid working from a modern London office.
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