At a Glance
- Tasks: Write production code and build data pipelines that drive insights for clients.
- Company: Codat, a cutting-edge advisory intelligence solution backed by industry giants.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Join a dynamic team focused on innovation and collaboration.
- Why this job: Make a real impact by solving user problems with your code every day.
- Qualifications: Strong coding skills in Python or C#, and experience with data engineering tools.
The predicted salary is between 36000 - 60000 £ per year.
About Codat
Codat is an advisory intelligence solution purpose-built for modern commercial banking. Through rich, specialized data, forward-looking insights, and integrated workflows, Codat empowers banking teams to deepen their relationships, grow their revenue, and simplify their day-to-day work. Founded in 2017 and backed by JPMorgan, PayPal, Amex, Plaid, and Shopify, Codat has successfully powered over 350,000 connections to business customers' financial systems — and is trusted by industry leaders to turn scattered information into actionable, strategic advantages in real time, every time.
The Role
We’re looking for a Senior Data Engineer to join our Insights team. You’ll be hands-on every day — writing production code, building and maintaining data pipelines, and shipping features that turn raw data into actionable intelligence for our clients. You’ll work across the full project lifecycle, from understanding the problem through to delivery, and you’ll care as much about code quality and operational reliability as you do about getting things shipped.
This isn’t a platform architecture role. You’ll be building and owning pipelines end-to-end, not designing abstractions for other engineers to build on. You’ll thrive if you’re motivated by solving real user problems and you want to work somewhere your code has direct, visible business impact.
What You’ll Do
- Write production code daily, most likely in Python, building and maintaining the data pipelines that power our Insights products.
- Own the full lifecycle of your projects: understanding the data domain, designing pragmatic solutions, shipping them, and keeping them running reliably.
- Drive technical quality through strong engineering practices — testing, observability, data quality checks, and clean, maintainable code.
- Collaborate with product, data science, and engineering stakeholders to shape what we build and how we build it.
- Identify opportunities to apply AI within our products and workflows where it delivers genuine value.
- Contribute to the growth of the team by sharing knowledge and championing good engineering practices.
What You’ll Bring
- Strong software engineering fundamentals: you write well-tested, production-ready code and care about maintainability, observability, and operational excellence.
- Solid experience with modern data engineering tools and patterns — some combination of SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), and DBT.
- Proficiency in a strongly typed language, ideally Python or C#.
- Comfort with modern deployment practices: CI/CD, containerisation (Docker), and cloud-based infrastructure.
- A product mindset — you want to understand the business domain and use that understanding to influence what you build, not just how you build it.
- The ability to communicate clearly with both technical and non-technical colleagues.
Senior Data Engineer in London employer: Codat
Codat is an exceptional employer that fosters a culture of technical excellence and continuous improvement, making it an ideal place for Frontend Engineers looking to make a significant impact. With a strong emphasis on mentorship and collaboration, employees are encouraged to grow their skills while working on innovative projects in a fast-paced environment. The company's backing by industry leaders and its commitment to leveraging cutting-edge technologies provide unique opportunities for professional development and meaningful contributions to the future of commercial banking.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Codat.
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We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Codat, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Codat. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Codat
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Codat!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
