At a Glance
- Tasks: Extract and model data from complex legacy systems for an AI startup.
- Company: Fast-growing, VC-backed AI startup in London with a dynamic culture.
- Benefits: Early equity, discretionary bonuses, pension matching, and private health cover.
- Other info: Hybrid working model with opportunities for career growth and autonomy.
- Why this job: Join a pioneering team and make a real impact in a safety-critical sector.
- Qualifications: Experience with legacy systems, ETL processes, and backend services required.
The predicted salary is between 72000 - 88000 £ per year.
We're hiring for a fast-growing, VC-backed startup building AI-powered software for a safety-critical sector. This is currently the most business-critical technical hire on their roadmap, tied to a live enterprise deployment.
You’ll be:
- Extracting data from legacy, semi-on-prem, non-uniform systems where APIs are often limited or non-existent, using non-standard ingestion routes rather than a clean API-first approach.
- Building data models, pipelines, and last-mile integrations/connectors across genuinely fragmented, real-world infrastructure, not a clean greenfield stack.
- Owning the back-end services those pipelines run on, including infrastructure as code.
- Handling ETL, schema mapping, and reconciliation across legacy and modern systems side by side.
- Working with zero-copy and data virtualisation approaches where direct extraction isn't possible.
- Operating in short iterative cycles with high autonomy and no fixed playbook.
Core skills:
- Genuine experience getting data out of legacy or undocumented systems without relying on modern APIs, screen-scraping, UI automation, batch exports, direct database access, whatever the environment demands.
- Production back-end services experience (Node/TypeScript or Python), including infrastructure as code (Terraform or Pulumi).
- Data modelling, legacy systems, backend-to-warehouse flows.
- ETL, schema mapping, and reconciliation across old and new systems.
- Solid AWS/cloud, end-to-end across the stack: VPC, ECS, Lambda, S3, KMS.
- Security awareness: GuardDuty, SecurityHub or equivalent.
- Data warehousing (Redshift, Glue, Synapse or Snowflake) and orchestration (Airflow, dbt or Prefect).
- Comfort with streaming/connectivity (Kafka, JDBC/ODBC) and data quality/schema tooling (Great Expectations, Pydantic, Avro/Protobuf).
Strong plus, not required:
- Regulated data experience (law enforcement, health, legal, fintech, government).
- Event or temporal data modelling.
- UI-based legacy ingestion tooling specifically.
- Dual cloud and on-prem deployment experience.
What we’re looking for:
A blend of startup pace and larger-company depth. Comfortable owning ambiguity, but able to handle complex, regulated environments.
Compensation:
- Early equity allocation, with a commitment to top up early joiners further.
- Discretionary bonus once revenue begins.
- Pension matching, private health and dental cover.
- Hybrid working, London preferred, flexibility for strong senior candidates elsewhere in the UK provided they’re well-connected and open to occasional travel.
Must-have:
Able to attain security clearance (UK national or 3+ years continuous UK residency), security clearance required, no visa sponsorship, no exceptions on this one.
Founding Data Engineer in London employer: Wave Group
Wave Group is an excellent employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. Employees benefit from competitive salaries, flexible hybrid working arrangements, and opportunities for professional growth while contributing to impactful projects that modernize policing through advanced AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Data Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Wave Group!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Founding Data Engineer at Wave Group.
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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 Wave Group.
✨Apply Directly through Our Website
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We think you need these skills to ace Founding 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 Wave Group, 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 Wave Group. 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 Wave Group
✨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 Wave Group!
✨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.
