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For Companies At a Glance
- Tasks: Design and develop data models, build data pipelines, and automate workflows.
- Company: Dynamic fintech company in the heart of London.
- Benefits: Competitive salary, full-time role, and opportunities for professional growth.
- Why this job: Join a growing team and make a real impact on our data platform's evolution.
- Qualifications: 5 years in data roles, strong SQL and Python skills, and cloud platform experience.
- Other info: Fast-paced environment with exciting projects and career advancement opportunities.
The predicted salary is between 78000 - 104000 £ per year.
Location: City Of London
Employment Type: Full-time
Salary: £90,000 - £100,000
Sector: Fintech / Payments
Overview
We are looking for a highly skilled Lead Data Engineer with a strong foundation in data analytics to join a growing team. The ideal candidate will have previously worked as a Data Analyst and since transitioned into a more engineering-focused role. You will help us scale our data infrastructure, design and build robust data models, and contribute directly to our data platform's evolution. This is a hands-on role where you will be expected to hit the ground running, contribute to ongoing projects with minimal hand-holding, and help us maintain (and improve) the current team's velocity.
Key Responsibilities
- Design, develop, and maintain data models to support analytical and operational use cases.
- Write efficient, production-grade SQL to build data pipelines and transformations.
- Develop and maintain data workflows and automation scripts in Python.
- Collaborate with analysts, engineers, and stakeholders to deliver high-quality data solutions.
- (Optional but highly valued) Contribute to our infrastructure as code efforts using tools like Terraform.
- Work with modern data warehousing technologies such as Snowflake to ensure scalable and high-performing solutions.
Skills & Experience
- 5 years of experience in data roles, ideally transitioning from Data Analyst to Data Engineer.
- Proven expertise in SQL and building complex data models.
- Strong proficiency in Python for data processing, ETL, and workflow automation.
- Experience with cloud data platforms (Snowflake experience highly desirable).
- Exposure to or experience with Terraform or similar infrastructure-as-code tools is a strong plus.
- Comfortable working in fast-paced environments and able to contribute quickly without extensive onboarding.
Nice to Have
- Experience with modern data stack tools (e.g., dbt, Airflow, etc.).
- Understanding of CI/CD pipelines and data infrastructure automation.
- Familiarity with data governance, security, and best practices in a cloud environment.
Lead Data Engineer in London employer: 83zero Ltd
Contact Detail:
83zero Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer in London
✨Network Like a Pro
Get out there and connect with people in the fintech space! Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your past projects, especially those where you’ve designed data models or built data pipelines. Use real examples to demonstrate how you can hit the ground running in a Lead Data Engineer role.
✨Tailor Your Approach
Make sure to tailor your conversations and presentations to the specific company and role. Research their tech stack and mention how your experience with SQL, Python, or Snowflake aligns with their needs. This shows you’re genuinely interested and ready to contribute.
✨Apply Through Our Website
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace Lead Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your journey from Data Analyst to Data Engineer. We want to see how your skills in data analytics have shaped your engineering capabilities, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for our team. Mention specific experiences that align with the role and show us your passion for data engineering.
Showcase Your Technical Skills: We’re looking for someone with solid SQL and Python skills, so make sure to highlight any relevant projects or achievements. If you've worked with Snowflake or Terraform, give us the details – we love seeing hands-on experience!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our awesome team at StudySmarter!
How to prepare for a job interview at 83zero Ltd
✨Know Your Data Inside Out
Make sure you brush up on your data analytics background. Be ready to discuss specific projects where you've designed and built data models, and how your analytical skills have helped in engineering roles. This will show that you can bridge the gap between analysis and engineering.
✨Show Off Your SQL Skills
Prepare to demonstrate your SQL prowess. Have examples ready of complex queries you've written or data pipelines you've built. Being able to talk through your thought process while solving a SQL problem can really impress the interviewers.
✨Python Proficiency is Key
Since Python is crucial for this role, be prepared to discuss your experience with it. Bring examples of automation scripts or ETL processes you've developed. If you can, even share snippets of code to illustrate your approach to data processing.
✨Familiarity with Modern Tools
If you've worked with tools like Snowflake, Terraform, or any modern data stack tools, make sure to highlight that experience. Discuss how these tools have improved your workflow and contributed to project success. It shows you're not just a data engineer but a forward-thinking one!
