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For Companies At a Glance
- Tasks: Own data transformation, build scalable models, and ensure high-quality datasets.
- Company: Join a pioneering fintech revolutionising private markets with data innovation.
- Benefits: Enjoy competitive salary, bonuses, 25 days holiday, and flexible hybrid working.
- Why this job: Be part of a fast-paced start-up, driving impactful decisions for top-tier investors.
- Qualifications: 2-4 years in analytics or data engineering, expert SQL skills, and dbt experience required.
- Other info: Opportunity for strong ownership and autonomy in your role.
The predicted salary is between 48000 - 84000 £ per year.
About the Opportunity
Join a pioneering fintech that's transforming private markets through data innovation. We're looking for a Data Analytics Engineer to own the transformation layer, deliver trusted datasets, and drive better decision-making for top-tier investors.
Key Responsibilities
- Build and maintain scalable, modular dbt models on Databricks and PostgreSQL
- Ensure high-quality, production-ready datasets through strong testing and observability practices
- Partner with stakeholders to define KPIs and develop reliable, actionable metrics
- Troubleshoot, monitor, and quickly resolve data inconsistencies or model failures
- Contribute to CI/CD pipelines and drive best practices across data governance and documentation
Tech Stack
- SQL
- dbt (Core)
- Python
- Databricks
- PostgreSQL
- Git + CI/CD
What We’re Looking For
- 2–4 years of experience in analytics engineering, data engineering, or a similar data-focused role
- Expert-level SQL skills with a focus on performance and scalability
- Hands-on experience using dbt in production environments
- Experience working with Databricks and/or PostgreSQL
- Strong understanding of data testing, observability, and quality assurance
- Familiarity with Git workflows and modern development practices
- Clear communicator with a collaborative approach
Bonus Skills
- Python scripting
- Cloud experience (preferably Azure)
- Knowledge of Private Equity or accounting concepts
What’s on Offer
- Fast-paced, high-growth start-up environment
- Strong ownership and autonomy in your role
- Competitive salary, discretionary bonus, pension, and long-term incentive opportunities
- 25 days holiday
- Flexible hybrid working model
Data Analytics Engineer employer: Albert Bow
Contact Detail:
Albert Bow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analytics Engineer
✨Tip Number 1
Familiarise yourself with the tech stack mentioned in the job description. Make sure you have hands-on experience with SQL, dbt, Databricks, and PostgreSQL. Consider working on personal projects or contributing to open-source projects that utilise these technologies to showcase your skills.
✨Tip Number 2
Network with professionals in the fintech and private equity sectors. Attend industry meetups or webinars to connect with potential colleagues or mentors. This can provide insights into the company culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Prepare to discuss your experience with data testing and observability practices. Be ready to share specific examples of how you've ensured data quality in previous roles. This will demonstrate your understanding of the importance of reliable datasets in decision-making.
✨Tip Number 4
Showcase your collaborative skills by preparing examples of how you've worked with stakeholders to define KPIs and develop metrics. Highlighting your communication abilities will help you stand out as a candidate who can effectively partner with others in the organisation.
We think you need these skills to ace Data Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in analytics engineering and data-focused roles. Emphasise your SQL skills, dbt experience, and any work with Databricks or PostgreSQL.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data innovation and how your skills align with the company's mission. Mention specific projects where you've successfully built scalable models or improved data quality.
Highlight Technical Skills: In your application, clearly list your technical skills, especially those mentioned in the job description like SQL, dbt, and Git workflows. Provide examples of how you've used these tools in past roles.
Showcase Collaboration Experience: Since the role requires partnering with stakeholders, include examples of how you've effectively communicated and collaborated with teams to define KPIs and develop actionable metrics.
How to prepare for a job interview at Albert Bow
✨Showcase Your SQL Skills
As a Data Analytics Engineer, your SQL expertise is crucial. Be prepared to discuss specific projects where you've optimised queries for performance and scalability. Highlight any challenges you faced and how you overcame them.
✨Demonstrate Your dbt Experience
Since the role requires hands-on experience with dbt, come ready to share examples of dbt models you've built or maintained. Discuss your approach to ensuring high-quality datasets and any testing practices you've implemented.
✨Communicate Clearly and Collaboratively
This position involves partnering with stakeholders, so it's essential to demonstrate your communication skills. Prepare to explain how you've worked with others to define KPIs and develop actionable metrics in past roles.
✨Familiarise Yourself with the Tech Stack
Make sure you're comfortable discussing the technologies mentioned in the job description, such as Databricks and PostgreSQL. If you have experience with cloud platforms like Azure, be ready to mention that too, as it could set you apart.
