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For Companies At a Glance
- Tasks: Lead and innovate in data engineering, transforming our data strategy and platform.
- Company: Join LendInvest, the UK's top FinTech platform revolutionising property finance.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a fun, collaborative culture with excellent career advancement opportunities.
- Why this job: Make a real impact on data integrity and decision-making in a dynamic environment.
- Qualifications: Expertise in Python, SQL, and cloud-based data platforms required.
The predicted salary is between 60000 - 80000 ÂŁ per year.
LendInvest is the UK’s leading FinTech platform for property finance. Over the past 17 years, we have grown from just our two founders to a team of over 200 working to make property finance simple for everyone. A workplace culture built around trying new things, getting things done, and having fun while we do it has helped us lend more than £7.5 billion of mortgages, put thousands of new or improved homes into the UK housing market, and successfully launch on the London Stock Exchange. We have big plans to continue growing the business, our products, our technology, and our people.
About your work
Reporting to the Head of Engineering, this is a critical “doer-leader” position focused on stabilising and remediating our data foundations while shaping our long‑term data strategy. This role is ideally suited to a current Senior or Lead Data Engineer ready to take on team leadership or an existing Data Team Lead looking for a new challenge. You will begin as a hands‑on technical lead, with a clear path to owning the data platform and building and leading the team around it. You will inherit a complex architectural landscape and play a key technical role working alongside our architecture team for our 2026 Data Transformation Programme. Initially, you will own technical direction, challenging external partners where required to remediate legacy ingestion issues. Following the initial transformation phase, you will take full ownership of the platform, ensuring data integrity and improving confidence in data‑driven decision making across the business.
Key Responsibilities
- Partner with external delivery specialists to troubleshoot and resolve "inherited" ingestion failures and silent data mutations.
- Take responsibility for a complex data ecosystem, addressing legacy ingestion patterns while incrementally building towards a more scalable, maintainable, and well‑architected platform.
- Automate manual data reconciliations and implement robust observability, testing, and validation frameworks to detect silent data issues, enforce data integrity, and improve trust in our pipelines.
- Manage the transition from partner‑led delivery to a sustainable internal "run" model, ensuring knowledge is fully transferred, documented, and embedded within the team.
- Build and scale a new internal data engineering function (initially hiring 1-2 engineers), reducing reliance on external partners.
- Establish engineering standards and challenge existing practices where necessary, and upskill Data Analysts to ensure insights are built on a governed, high‑trust data foundation.
About you
- Expertise in Python (or similar) and advanced SQL, with experience building and maintaining reliable, well‑structured data pipelines and transformation layers.
- Hands‑on experience designing and operating cloud‑based data platforms (e.g., AWS + modern warehouse), including orchestration, storage, and compute.
- Lead by example, setting engineering standards, mentoring others, and helping build a high‑performing data engineering capability.
- Experience applying testing, CI/CD, infrastructure as code, and version control to data platforms to ensure reliability and maintainability.
- Track record of implementing data validation, observability, and lineage to improve data trust and transparency.
- Comfortable working with existing platforms, identifying root causes of instability or inefficiency, and incrementally improving them.
- Able to work closely with analysts, product, and engineering teams to align data solutions with business needs.
Benefits
Data Lead employer: LendInvest
Contact Detail:
LendInvest Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Lead
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with LendInvest folks on LinkedIn. You never know who might give you a heads-up about an opportunity or refer you directly.
✨Tip Number 2
Prepare for those interviews by practising common data engineering questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format and types of questions you'll face.
✨Tip Number 3
Showcase your projects! Whether it's a GitHub repo or a personal website, having a portfolio of your work can really set you apart. Make sure to highlight any relevant experience with Python, SQL, and cloud-based platforms.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the LendInvest team.
We think you need these skills to ace Data Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Lead role. Highlight your experience with Python, SQL, and cloud-based data platforms. We want to see how your skills align with our needs, so don’t hold back!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our mission at LendInvest. We love seeing personality, so let your enthusiasm come through.
Showcase Your Achievements: When detailing your past roles, focus on specific achievements that demonstrate your ability to lead and improve data systems. We’re looking for results, so quantify your successes where possible!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at LendInvest
✨Know Your Data Inside Out
Before the interview, make sure you’re well-versed in the data landscape of LendInvest. Familiarise yourself with their existing data platforms and any recent changes in their architecture. This will not only show your genuine interest but also allow you to discuss how your experience can directly address their current challenges.
✨Showcase Your Leadership Skills
As a Data Lead, you'll need to demonstrate your ability to lead a team effectively. Prepare examples from your past experiences where you've successfully managed projects or mentored others. Highlight how you’ve built high-performing teams and established engineering standards, as this aligns perfectly with what they’re looking for.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about Python, SQL, and cloud-based data platforms. Brush up on your knowledge of data pipelines, CI/CD processes, and data validation techniques. Be ready to explain your thought process when troubleshooting data issues, as this will showcase your problem-solving skills.
✨Align with Their Culture
LendInvest values a culture of trying new things and having fun while getting things done. During the interview, share your own experiences that reflect this mindset. Discuss how you’ve embraced innovation in your previous roles and how you plan to foster a positive team environment while driving results.