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For Companies At a Glance
- Tasks: Build and optimise data pipelines using Python, SQL, and GCP for financial services.
- Company: Join a leading financial services firm focused on innovation and data-driven solutions.
- Benefits: Competitive pay, fully remote work, and opportunities for professional growth.
- Why this job: Make an impact in the finance sector by transforming complex data into actionable insights.
- Qualifications: Experience with Python, SQL, and cloud platforms; knowledge of actuarial and asset management.
- Other info: Enjoy a flexible, dynamic work environment with rolling contract options.
The predicted salary is between 48000 - 72000 £ per year.
Overview
Senior Data Engineer – Python – GCP – Databricks – Actuarial and Asset Management Excel Files – Investment/Financial/Insurance Industry Experience
Our client in the financial services space are looking for a Senior Data Engineer with experience in Actuarial and Asset Management Excel Files. As well as a strong background with Python, SQL, GCP and Databricks, working on large-scale, complex datasets and building end-to-end data pipelines in financial services environments, including automating processes, integrating multiple data sources, and delivering actionable insights to senior stakeholders.
Key Skills
- Actuarial and Asset Management Excel Files
- Investment & Financial domain knowledge: Have worked within the operations team for an asset management department and understands assets data, like financial securities
- SQL: Data manipulation and querying
- Python: Experience in libraries like Pandas and NumPy
- Cloud Platform: Building on GCP using BigQuery
- Familiarity with tools like DBT and Databricks
- Experience with investment-related projects or working in the reinsurance or life insurance domain
Rate – DoE Outside IR35
Location – Full remote (UK based)
Duration – 6 months rolling
Apply for this role
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Senior Data Engineer - Outside IR35 employer: Orbis
Contact Detail:
Orbis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - Outside IR35
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services space, especially those who work with data engineering. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Python, SQL, and GCP. Highlight any experience with Databricks and actuarial data. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss how you've built data pipelines and automated processes in previous roles. We want to see your problem-solving skills in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Engineer - Outside IR35
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and GCP. We want to see how you've tackled large-scale datasets and built data pipelines in the financial services sector.
Showcase Relevant Projects: Include specific examples of projects where you've worked with actuarial and asset management Excel files. This will help us understand your hands-on experience in the investment and financial domain.
Be Clear and Concise: When writing your cover letter, keep it straightforward. We appreciate clarity, so make sure you communicate your skills and experiences without any fluff.
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 this exciting opportunity.
How to prepare for a job interview at Orbis
✨Know Your Tech Stack
Make sure you brush up on your Python, SQL, and GCP skills. Be ready to discuss how you've used libraries like Pandas and NumPy in past projects. They’ll want to see your technical prowess, so prepare examples of how you've built data pipelines or automated processes.
✨Understand the Financial Landscape
Since this role is in the financial services sector, it’s crucial to have a solid grasp of actuarial and asset management concepts. Familiarise yourself with investment-related projects and be prepared to discuss how your experience aligns with their needs in managing complex datasets.
✨Showcase Your Problem-Solving Skills
Be ready to tackle hypothetical scenarios during the interview. Think about challenges you’ve faced in previous roles and how you overcame them, especially when integrating multiple data sources or delivering insights to stakeholders. This will demonstrate your analytical thinking and adaptability.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare insightful questions about their data strategies, team dynamics, or upcoming projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
