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- Tasks: Transform raw data into high-quality datasets and build scalable dbt models.
- Company: Join a leading data intelligence platform in the Private Equity sector.
- Benefits: Enjoy a competitive salary, bonus potential, and flexible remote work options.
- Why this job: Accelerate your career in a supportive environment with opportunities for learning and growth.
- Qualifications: 3+ years as a Data/Analytics Engineer, strong SQL skills, and experience with Databricks/PostgreSQL.
- Other info: Bonus points for knowledge of Private Equity and cloud data services.
The predicted salary is between 54000 - 84000 £ per year.
A data intelligence platform specialising in Private Equity is looking for a Data/Analytics Engineer.
You’ll transform raw data into meaningful, high-quality datasets that power applications across the company. You’ll build scalable dbt models on top of Databricks and PostgreSQL, partnering with data and business stakeholders to define metrics, track performance, and ensure data quality.
Working closely with the Head of Data and more senior colleagues across Data Engineering, Data Science and the wider Engineering and Product teams, you would be in an environment fostering learning and helping you accelerate your development and progression.
- At least 3 years professional experience as a Data Engineer or Analytics Engineer
- Strong proficiency in SQL, with proven experience writing complex, performant queries
- Experience working with Databricks and/or PostgreSQL
- Solid understanding of data testing, observability, and data quality assurance
- Familiarity with Git and modern software development practices
- At least intermediate proficiency in Python
Bonus points for experience with:
- Understanding of Private Equity and/or financial accounting
- Familiarity with data warehouse design and modelling
- Familiarity with cloud data services (preferably Azure)
Data Analytics Engineer SQL employer: Wave Talent
Contact Detail:
Wave Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analytics Engineer SQL
✨Tip Number 1
Make sure to brush up on your SQL skills, especially complex queries. You might want to prepare some examples of your past work where you've optimised queries or improved performance, as this will show your proficiency.
✨Tip Number 2
Familiarise yourself with Databricks and PostgreSQL if you haven't already. Consider working on a small project or two using these technologies to demonstrate your hands-on experience during discussions.
✨Tip Number 3
Since the role involves collaboration with various teams, think about how you can showcase your teamwork skills. Prepare examples of how you've successfully partnered with stakeholders in previous roles to achieve common goals.
✨Tip Number 4
If you have any experience with cloud data services, particularly Azure, be ready to discuss it. Even if it's not a primary requirement, showing familiarity can set you apart from other candidates.
We think you need these skills to ace Data Analytics Engineer SQL
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Data Engineer or Analytics Engineer, focusing on your proficiency in SQL and any relevant projects you've worked on with Databricks and PostgreSQL.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific experiences that demonstrate your skills in data testing, observability, and quality assurance, as well as your familiarity with Git and Python.
Showcase Relevant Projects: If you have worked on projects related to data warehouse design, modelling, or cloud data services, be sure to include these in your application. Highlight how these experiences align with the job requirements.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial in data analytics roles.
How to prepare for a job interview at Wave Talent
✨Showcase Your SQL Skills
Since strong proficiency in SQL is a key requirement, be prepared to discuss your experience with complex queries. You might even be asked to solve a SQL problem on the spot, so brush up on your skills and think through your approach to writing performant queries.
✨Demonstrate Your Experience with Databricks and PostgreSQL
Make sure to highlight any projects where you've used Databricks or PostgreSQL. Be ready to explain how you built scalable models and the impact they had on data quality and performance within your previous roles.
✨Discuss Data Quality Assurance
Understanding data testing and observability is crucial for this role. Prepare examples of how you've ensured data quality in past projects, including any specific tools or methodologies you used to monitor and maintain data integrity.
✨Familiarity with Git and Collaboration
As modern software development practices are important, be ready to talk about your experience with Git. Discuss how you've collaborated with teams in the past, especially in terms of version control and code reviews, to show that you're a team player.
