At a Glance
- Tasks: Design and optimise Snowflake data solutions for finance and insurance sectors.
- Company: Albany Beck, a leading Financial Services Consultancy focused on transformation.
- Benefits: Meaningful career growth, competitive salary, and commitment to your development.
- Other info: Collaborative environment with opportunities for innovation and professional development.
- Why this job: Join a passionate team making impactful changes in the financial industry.
- Qualifications: 2+ years Snowflake experience and 5+ years in London Market insurance.
The predicted salary is between 63000 - 77000 £ per year.
Albany Beck is a specialist Financial Services Consultancy helping institutions deliver complex change and transformation while building the internal capability to sustain it.
We combine subject matter expertise with innovative delivery models that help clients scale efficiently, while offering meaningful, long-term career opportunities to our people.
At Albany Beck, you’ll be choosing to work with an organisation that’s passionate about your development and committed to delivering meaningful outcomes for our clients.
Role Overview
We are seeking a highly experienced Senior Snowflake Data Engineer to support the delivery and expansion of an enterprise data platform.
The individual will play a key role in designing, building and optimising Snowflake-based data solutions that support Underwriting, Claims, Finance, Portfolio Management and Delegated Authority reporting.
The role requires a strong combination of hands‑on Snowflake engineering expertise and deep London Market insurance knowledge to ensure business requirements are translated into scalable, trusted and well‑governed data products.
The successful candidate will work closely with Data Product, Analytics, Data Governance, Architecture and business stakeholders.
Responsibilities
- Design, develop and maintain scalable
Snowflake data pipelines and ELT processes .
- Develop and optimise Snowflake data models across Raw, Curated and Gold layers.
- Implement reusable engineering patterns, frameworks and deployment processes.
- Support platform scalability, performance tuning and cost optimisation.
- Build and maintain automated data quality, reconciliation and monitoring capabilities.
- Support historisation, snapshotting and auditability requirements across the platform.
- Contribute to Dev Ops, CI/CD and release management processes for Snowflake deployments.
- Data Integration
- Integrate business data from core insurance platforms and external sources into Snowflake.
- Develop ingestion and transformation processes using
Azure Data Factory, Snowflake and associated tooling .
- Support integration of submission, policy, premium, claims, bordereaux, delegated authority and finance datasets.
- Assist with migration and reconciliation activities between the legacy on-premise data warehouse and Snowflake.
- Implement enterprise data models aligned to underwriting, claims and finance requirements.
- Develop conformed dimensions and reusable business entities.
- Support semantic model requirements for Power BI and analytical consumption.
- Apply best practice modelling approaches including dimensional, star schema and Snowflake modelling techniques.
- Snowflake — Key Requirement
- Minimum
2+ years hands‑on Snowflake engineering experience in a production environment.
- Strong experience designing and building enterprise‑scale Snowflake platforms.
• Strong hands‑on experience with
- Snowflake performance optimisation
- Tasks and Streams
- Secure Views
- Data Sharing
- Cost optimisation
- Data governance implementation
- Role‑based access controls
- Metadata management
- London Market Insurance
- Minimum
5+ years London Market insurance experience .
• Strong understanding of
- Premiums
- Claims
- UMRs
- Lloyd's and Company market operations
- Experience working with Underwriting, Claims and Finance stakeholders.
- Experience building enterprise ETL/ELT pipelines.
- Experience implementing data quality frameworks and reconciliation processes.
- Experience with version control and Dev Ops practices.
- Experience working within modern cloud data platforms.
- Apply best practice modelling approaches including dimensional, star schema and Snowflake modelling techniques.
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Snowflake Data Engineer employer: Albany Beck
Albany Beck is an exceptional employer that fosters a collaborative work culture, empowering employees to drive impactful change within the financial services sector. With a focus on professional growth, team members are encouraged to develop their skills through involvement in large-scale transformation programmes across European regulatory frameworks, ensuring meaningful contributions to both client success and personal career advancement.
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We think this is how you could land Snowflake Data Engineer
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Snowflake Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Albany Beck. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Albany Beck
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Albany Beck!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
