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- Tasks: Build and maintain data pipelines for product and analytics use cases.
- Company: Mission-driven tech company focused on AI-led intelligence and sustainability.
- Benefits: Competitive salary, equity, hybrid working, and growth opportunities.
- Other info: Collaborative environment with a focus on ownership and innovative engineering.
- Why this job: Join a small team and tackle exciting data challenges with real-world impact.
- Qualifications: Strong Python and SQL skills; experience in AWS preferred.
The predicted salary is between 60000 - 70000 £ per year.
An early-stage, mission-driven technology company is building an AI-led intelligence platform designed to bring transparency to a highly complex global industry. With sustainability at its core, the platform enables large organisations to make better, more responsible decisions by combining real-time data, pricing intelligence, and policy insight.
With an MVP live, early enterprise customers engaged, and strong funding in place, the company is now focused on strengthening the data foundations that underpin the product and its future AI roadmap. This role will be one of the first dedicated data engineering hires. You will work closely with senior technical leadership to build reliable data pipelines, improve data quality, and enable analytics, product features, and machine-learning use cases as the platform evolves.
Role- Build and maintain data pipelines that ingest, transform, and serve data for product and analytics use cases.
- Integrate multiple internal and external data sources into a clean, reliable data layer.
- Work closely with engineering and product teams to ensure data supports real-world decision making.
- Help establish best practices around data modelling, transformation, and quality checks.
- Contribute to the foundations that will support future machine-learning and AI initiatives.
- Strong experience with Python and SQL.
- Solid data engineering fundamentals and experience building production data pipelines.
- Experience working in AWS or another major cloud environment.
- Comfortable operating in an evolving system where some foundations are still being built.
- A collaborative mindset and interest in understanding how data is used across the product.
- Familiarity with managed or open-source data ingestion tools (for example Fivetran, Airbyte, or similar).
- Exposure to data used in analytics or machine-learning contexts.
- Experience working in early-stage or fast-moving product teams.
- A role with genuine scope to grow as the data function expands.
- Close collaboration with experienced engineering and AI leadership.
- Exposure to technically interesting data problems with real-world impact.
- Equity alongside a competitive salary.
- Hybrid working, typically two days per week in London.
- A small, senior team that values ownership, honesty, and thoughtful engineering.
Unfortunately, sponsorship is not available.
Seniority level: Entry level
Employment type: Full-time
Job function: Information Technology
Industries: Staffing and Recruiting
Location: London, England, United Kingdom
Data Engineer in London employer: SENZO
Contact Detail:
SENZO Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Python and SQL. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in our mission-driven approach. Tailor your application to highlight how your skills align with our goals in building a sustainable AI-led platform.
We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and data engineering fundamentals. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re passionate about data engineering and how you can contribute to our mission. Keep it concise but engaging, and don’t forget to mention any experience with AWS or cloud environments!
Showcase Your Collaborative Spirit: Since we value teamwork, make sure to highlight any experiences where you’ve worked closely with product or engineering teams. We love candidates who understand the importance of collaboration in building reliable data pipelines.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at SENZO
✨Know Your Data Engineering Fundamentals
Brush up on your data engineering basics, especially around building production data pipelines. Be ready to discuss your experience with Python and SQL, as these are core skills for the role. Prepare examples of how you've used these technologies in past projects.
✨Familiarise Yourself with the Company’s Mission
Since this is a mission-driven tech company, understanding their focus on sustainability and transparency will help you align your answers with their values. Think about how your work can contribute to responsible decision-making in the industry.
✨Prepare for Technical Questions
Expect technical questions related to AWS or other cloud environments. Review common data ingestion tools like Fivetran or Airbyte, even if they’re not mandatory. Being able to discuss these tools will show your proactive approach and willingness to learn.
✨Show Your Collaborative Spirit
This role requires a collaborative mindset, so be prepared to share examples of how you've worked with cross-functional teams in the past. Highlight your interest in understanding how data impacts product features and decision-making processes.