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For Companies At a Glance
- Tasks: Transform financial processes into automated workflows and create impactful data visualisations.
- Company: Join a leading firm in life reinsurance, based in Bermuda.
- Benefits: Fully remote work, competitive pay, and long-term contract opportunities.
- Why this job: Make a real difference by building scalable data infrastructure for global clients.
- Qualifications: 4+ years in data engineering, strong SQL skills, and experience with BI tools.
- Other info: Embrace a collaborative culture with opportunities for growth and learning.
Delivering scalable data infrastructure that transforms manual financial and actuarial processes into automated, auditable workflows. To deliver robust, scalable backend systems and data infrastructure that power automated data pipelines and dashboards for our global life reinsurance client in Bermuda.
Responsibilities
- Designing and implementing data warehouse schemas in cloud environments (BigQuery preferred)
- Building reconciliation and data quality frameworks for financial data
- Creating dashboards and data visualisations for business stakeholders
- Working with financial instrument identifiers (ISIN, CUSIP), rating agencies, and cross-system data mapping
Requirements
Must Have Experience:
- 4+ years experience in data engineering or data architecture roles
- Strong SQL skills with experience designing data warehouse schemas (BigQuery, Snowflake, or similar)
- Proven experience with dbt for data transformation workflows
- Asset management or financial markets experience (e.g. investment accounting, fund administration, portfolio management)
- Experience building reconciliation logic and data quality frameworks
- Proficiency with BI tools (Looker, Looker Studio, or similar)
Bonus (the Nice To Haves)
- Insurance or reinsurance industry experience
- Knowledge of Clearwater, Aladdin, and other finance systems
- Familiarity with regulatory reporting (IFRS 17, BSCR, Solvency II)
- Python proficiency for data processing and automation
- Experience with GCP services (Cloud Storage, Pub/Sub, Cloud Run)
Required Behaviours/Characteristics
- Curious: Proactively explores problems and technologies; asks good questions
- Hard-working: Delivers reliably and takes ownership of outcomes
- Adaptable: Comfortable with ambiguity and evolving requirements; learns new domains quickly
- Collaborative: Works effectively with data engineers, analysts, and client stakeholders
- Quality-focused: Writes clean, tested, maintainable code
Benefits
- Fully Remote
- Outside IR35
- Long term contract
- £600 - £650/Day
Senior Data Analyst & Architect employer: Toucanberry Tech
Contact Detail:
Toucanberry Tech Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analyst & Architect
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering and architecture space. Attend meetups or webinars related to financial data, and don’t be shy about asking for introductions. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best work with data warehouse schemas and dashboards. Use platforms like GitHub to share your projects. This gives potential employers a taste of what you can do, and we love seeing your creativity in action!
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and dbt skills. Practice common data engineering scenarios and be ready to discuss your experience with financial data. We want to see how you tackle real-world problems, so think through your past projects and be ready to share!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who are eager to transform financial processes into automated workflows. Let’s make data magic happen together!
We think you need these skills to ace Senior Data Analyst & Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Analyst & Architect role. Highlight your SQL prowess, data warehouse design experience, and any relevant financial markets background to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Share specific examples of your past work with data pipelines and dashboards, and how they relate to what we do at StudySmarter.
Showcase Your Projects: If you've worked on any cool projects involving data engineering or architecture, don’t hold back! Include links or descriptions in your application to give us a taste of your hands-on experience and creativity.
Apply Through Our Website: We love it when you apply directly through our website! It helps us keep track of your application and ensures you get all the updates. Plus, it shows us you're keen on joining the StudySmarter team!
How to prepare for a job interview at Toucanberry Tech
✨Know Your Data Inside Out
Make sure you’re well-versed in data engineering and architecture concepts, especially around SQL and data warehouse schemas. Brush up on your experience with BigQuery or similar platforms, as you’ll want to impress them with your technical knowledge.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in the past. They’ll be looking for someone who is curious and proactive, so share specific instances where you explored new technologies or solved tricky problems.
✨Demonstrate Your Collaborative Spirit
Since this role involves working closely with various stakeholders, be ready to discuss how you’ve successfully collaborated with teams in the past. Highlight your adaptability and how you’ve navigated ambiguity in projects.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions, especially around data quality frameworks and reconciliation logic. Practise articulating your thought process clearly, as they’ll want to see how you approach building robust systems.
