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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 office days.
- Why this job: Accelerate your career in a collaborative environment with opportunities for learning and growth.
- Qualifications: 3-5 years experience in Data/Analytics Engineering, strong SQL skills, and proficiency in Python.
- Other info: This role does not offer VISA sponsorship.
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. This role would be perfect for someone with 3-5 years experience, looking to take their career to the next level. 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.
- Must have requirements:
- 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 DBT in production
- 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
- Strong communication skills and the ability to collaborate across teams
- At least intermediate proficiency in Python
- Bonus points for experience with:
- Understanding of Private Equity and/or financial accounting
- Experience manipulating, processing, modelling, and extracting value from large, disconnected datasets
- Familiarity with data warehouse design and modelling
- Familiarity with cloud data services (preferably Azure)
- Experience with Airflow
Please note: unfortunately, this role does not offer VISA sponsorship.
Data/Analytics Engineer employer: Wave Talent
Contact Detail:
Wave Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data/Analytics Engineer
✨Tip Number 1
Network with professionals in the Private Equity and Financial Services sectors. Attend industry meetups or webinars to connect with potential colleagues and learn more about the specific challenges they face, which can help you tailor your approach during interviews.
✨Tip Number 2
Familiarise yourself with the tools mentioned in the job description, especially Databricks and PostgreSQL. Consider working on personal projects or contributing to open-source projects that utilise these technologies to demonstrate your hands-on experience.
✨Tip Number 3
Prepare to discuss your previous experiences with data quality assurance and testing. Be ready to share specific examples of how you've ensured data integrity in past roles, as this is a key requirement for the position.
✨Tip Number 4
Showcase your communication skills by preparing to explain complex technical concepts in simple terms. This will be crucial when collaborating with business stakeholders, so practice articulating your thoughts clearly and concisely.
We think you need these skills to ace Data/Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Data Engineer or Analytics Engineer. Focus on your proficiency in SQL, DBT, Databricks, and PostgreSQL. Use specific examples to demonstrate your skills in data testing and quality assurance.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your relevant experience and how it aligns with the job requirements. Highlight your strong communication skills and ability to collaborate across teams.
Showcase Relevant Projects: If you have worked on projects involving large datasets or cloud data services, be sure to include these in your application. Describe your role, the technologies used, and the impact of your work on the project outcomes.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial in data roles.
How to prepare for a job interview at Wave Talent
✨Showcase Your SQL Skills
Since strong proficiency in SQL is a must-have, 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 be ready to demonstrate your thought process.
✨Familiarise Yourself with DBT and Databricks
As this role involves building scalable dbt models on Databricks, make sure you understand how both tools work. Be ready to talk about any projects you've completed using these technologies and how they contributed to data quality and performance.
✨Communicate Clearly
Strong communication skills are essential for collaborating with various teams. Practice explaining technical concepts in simple terms, as you may need to convey complex ideas to non-technical stakeholders during the interview.
✨Demonstrate Your Problem-Solving Abilities
Be prepared to discuss past challenges you've faced in data engineering or analytics. Highlight how you approached these problems, the solutions you implemented, and the impact they had on your team or project.
