At a Glance
- Tasks: Design and own data architecture for a cutting-edge financial services platform.
- Company: Join a leading financial services firm with a focus on innovation.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a chance to mentor and lead teams.
- Why this job: Shape the future of finance with your expertise in data architecture.
- Qualifications: 15+ years IT experience, 5+ years as Data Architect, strong Snowflake skills.
The predicted salary is between 90000 - 120000 £ per year.
We are looking for a Senior Data Architect (15+ years experience) to design and own the entire data architecture for a financial services platform covering: Accounts / Real-Time Ledger (RTL) Payments Engine. The architect will be responsible for how data is stored, moved, governed, secured, and consumed across operational systems and the enterprise data warehouse (Snowflake).
Key Skills
- Enterprise Data Platform
- ERD (Entity Relationship Diagrams)
- Data Flow Diagrams
- ADRs (Architecture Decision Records)
- Snowflake (Critical Skill)
- Snowflake Architecture
- Snowflake Data Warehouse
- Dynamic Tables
- Cortex AI
- Dynamic Data Masking
- Databases
- Apache Spark
- Event-Driven Architecture
- Lake Formation
- Feature Stores
- AI/ML Data Architecture
- Snowflake Cortex AI
- AI-Powered Data Cataloguing
- dbt (Data Build Tool)
Skills Required
- Schema Design
- Replication
- Database Performance Tuning
- Data Lifecycle Management
Tools
- Collibra
- Snowflake
- Horizon Catalog
Key Areas
- Testing Frameworks
- Documentation
- Financial Services Domain Experience (Very Important)
- Real-Time Ledger (RTL)
- Event-Sourced Ledger
- Balance Aggregation
- Payments
- Market Data Feeds
- Regulatory Reporting
- Client Onboarding
Key Responsibilities
- Establish data standards and governance frameworks.
- Define data ownership, lineage, and quality controls.
- Snowflake Leadership
- Design and optimize Snowflake architecture.
- Build ingestion frameworks and transformation standards.
- Implement security and compliance controls.
- Manage warehouse performance and costs.
- Database Governance
- Review database schemas and performance.
- Define migration and versioning standards.
- Ensure consistency between transactional and analytical systems.
- Data Governance
- Implement data quality rules and SLAs.
- Manage lineage and metadata.
- Support regulatory compliance requirements.
- AI & Analytics
- Design data products for reporting and analytics.
- Build foundations for ML and AI workloads.
- Support feature stores and LLM use cases.
- Stakeholder Management
- Work with Engineering, Risk, Finance, Operations, and Product teams.
- Mentor engineers and developers.
- Drive architecture decisions across the organization.
Ideal Candidate Profile
- 15+ years IT experience
- 5+ years as Data Architect
- Strong Snowflake Architecture experience
- Financial Services / Banking experience
- Data Governance and Data Quality expertise
Senior Data Architect employer: VBeyond Corporation
As a leading financial services provider, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel. Our Senior Data Architect role offers not only competitive benefits and opportunities for professional growth but also the chance to work with cutting-edge technologies like Snowflake and AI/ML frameworks in a dynamic environment. Join us in shaping the future of finance while enjoying a supportive atmosphere that values your contributions and encourages continuous learning.
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We think this is how you could land Senior Data Architect
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We think you need these skills to ace Senior Data Architect
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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How to prepare for a job interview at VBeyond Corporation
✨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!
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✨Get Comfortable with Python and R
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✨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.
