At a Glance
- Tasks: Build and maintain data pipelines to transform complex datasets into actionable insights.
- Company: Fast-growing private markets data platform revolutionising business intelligence.
- Benefits: Competitive salary up to £85,000 plus bonus and opportunities for professional growth.
- Other info: Collaborate with a dynamic team in a modern data stack environment.
- Why this job: Join a mission-driven team and shape the future of data infrastructure.
- Qualifications: 4+ years in Data Engineering, strong Python skills, and experience with DBT and Snowflake.
The predicted salary is between 85000 - 85000 £ per year.
We're partnering with a fast growing private markets data platform that is transforming how GPs and investors use business intelligence to make faster, better decisions. Their platform is trusted by leading private capital firms to deliver powerful insights built on centralised, validated data.
Following strong growth, they are now looking for a Data Engineer to join the team and help scale the data infrastructure that powers it all. Working across a modern data stack, you will design and maintain the pipelines, models and infrastructure that turn complex, disconnected datasets into reliable, actionable intelligence for the business and its customers.
What You'll Do
- Build and maintain data pipelines to extract, transform and load data from APIs, SFTP and databases at scale.
- Develop and maintain DBT models across an extensive library to support product and business requirements.
- Identify and implement process improvements including automating manual workflows and optimising data delivery.
- Build analytics models and tools that surface insights across customer acquisition, operational efficiency and key business metrics.
- Work with stakeholders across data, product and engineering to support data infrastructure needs.
- Design pipelines with a security first mindset to protect end user data.
What They Are Looking For
- 4+ years in a Data Engineering or Analytics Engineering role.
- Strong Python skills with a focus on code quality and testing.
- Hands on experience with DBT, Snowflake and PostgreSQL.
- Experience with data warehouse design, complex SQL and relational databases.
- Familiarity with Azure and version control via Git and GitHub.
- Bonus points for experience in financial services or private equity, Dagster or Prefect, or data governance tooling.
Why This Role Is Exciting
- Join a high growth SaaS platform transforming private markets data.
- Work with a modern, well considered data stack including Databricks, Fivetran and Snowflake.
- Collaborate closely with a technical and ambitious team on a real mission.
- Genuine opportunity to shape data infrastructure at an exciting stage of growth.
Data Engineer in London employer: Albert Bow
At Albert Bow, we pride ourselves on fostering a dynamic and collaborative work culture that empowers our employees to take ownership of their projects. Located in the vibrant Greater London area, we offer competitive benefits, opportunities for professional growth, and a chance to work with cutting-edge technology in a small, high-output team. Join us to make a meaningful impact while advancing your career in an innovative environment.
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, DBT, and Snowflake. 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 skills and understanding the company’s data stack. Be ready to discuss how you've tackled challenges in previous roles and how you can contribute to their mission.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, DBT, and any relevant data warehousing skills. We want to see how your background aligns with what we're looking for!
Showcase Your Projects:Include specific projects where you've built data pipelines or worked with complex SQL. This gives us a clear picture of your hands-on experience and how you can contribute to our team.
Be Clear and Concise:When writing your cover letter, keep it clear and to the point. Explain why you're excited about this role and how your skills can help us transform private markets data. We love enthusiasm!
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. We can't wait to hear from you!
How to prepare for a job interview at Albert Bow
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, DBT, Snowflake, and PostgreSQL. Brush up on your coding skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in previous roles. Think about specific instances where you improved processes or optimised data delivery, as this will demonstrate your ability to add value to their team.
✨Understand the Business Context
Familiarise yourself with the private markets data landscape and how data engineering plays a role in it. Being able to discuss industry trends and how they impact the company will show that you're not just a techie but also understand the bigger picture.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data infrastructure and future plans. This shows your genuine interest in the role and helps you assess if the company is the right fit for you. Plus, it gives you a chance to engage with your interviewers on a deeper level.
