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For Companies At a Glance
- Tasks: Design and modernise data architectures in the financial services sector.
- Company: Leading financial services firm focused on innovation and technology.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of data in finance.
- Qualifications: Experience with CDC, Db2, z/OS, and strong data modelling skills.
- Other info: Fast-paced environment with potential for significant career advancement.
The predicted salary is between 48000 - 72000 £ per year.
Ideal Background
- Financial services background (banking, payments, capital markets)
- Mix of mainframe and modern technology experience
- Track record of modernizing legacy systems
- Production support and incident management experience
Must-Have
- Change Data Capture: CDC design and operations (IBM, Precisely, or equivalent); subscription management, bookmarks, replay, backfill.
- Db2 & z/OS knowledge: Db2 catalog, z/OS fundamentals, batch windows, performance considerations.
- Integration patterns: Kafka/MSK hands-on, CDC-to-target pipelines, UPSERT/MERGE logic; Python/SQL; strong troubleshooting.
- Data quality mindset: Write validation tests before migration; golden-source reconciliation.
Data Architecture Fundamentals (Must-Have)
- Logical data modeling: Entity-relationship diagrams, normalization (1NF through Boyce-Codd/BCNF), denormalization trade-offs; identify functional dependencies and anomalies.
- Physical data modeling: Table design, partitioning strategies, indexes; SCD types; dimensional vs. transactional schemas; storage patterns for OLTP vs. analytics.
- Normalization & design: Normalize to 3NF/BCNF for transactional systems; understand when to denormalize for queries; trade-offs between 3NF, Data Vault, and star schemas.
- Domain-Driven Design: Bounded contexts and subdomains; aggregates and aggregate roots; entities vs. value objects; repository patterns; ubiquitous language.
- Event-driven architecture: Domain events and contracts; CDC as event streams; idempotency and replay patterns; mapping Db2 transactions to event-driven architectures; saga orchestration.
- CQRS patterns: Command/query separation; event sourcing and state reconstruction; eventual consistency; when CQRS is justified for mainframe migration vs. overkill.
- Database internals: Index structures (B-tree, bitmap, etc.), query planning, partitioning strategies; how Db2 vs. PostgreSQL differ in storage and execution.
- Data quality & validation: Designing test suites for schema conformance; referential integrity checks; sampling and reconciliation strategies.
Nice-to-Have
- None listed.
Data Architect employer: Bounteous
Contact Detail:
Bounteous Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services sector, especially those who know their way around data architecture. Attend meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your experience with CDC design, Db2, and event-driven architecture. Use real-world examples to demonstrate how you’ve tackled challenges in modernising legacy systems. This will make you stand out when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss integration patterns, logical and physical data modelling, and the trade-offs between different schemas. Practise explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly can sometimes give you a leg up in the hiring process. So, get your application in and let’s get you that dream job!
We think you need these skills to ace Data Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience in financial services and any relevant tech skills, especially around CDC design and Db2. We want to see how your background fits with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data architecture and how your skills align with our needs. Don't forget to mention your experience with modernising legacy systems and production support.
Showcase Your Projects: If you've worked on projects involving Kafka, Python, or SQL, make sure to include them! We love seeing real-world examples of your work, especially those that demonstrate your data quality mindset and troubleshooting skills.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best experience possible. Plus, we can't wait to see what you bring to the table!
How to prepare for a job interview at Bounteous
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Change Data Capture and Db2. Brush up on your knowledge of integration patterns like Kafka and how to troubleshoot them effectively.
✨Showcase Your Financial Services Experience
Since a financial services background is ideal, be ready to discuss your previous roles in banking or payments. Highlight any specific projects where you modernised legacy systems or managed production support.
✨Demonstrate Your Data Modelling Skills
Prepare to talk about logical and physical data modelling. Bring examples of entity-relationship diagrams you've created and discuss your approach to normalisation and denormalisation in past projects.
✨Think Like a Data Architect
During the interview, frame your answers around data architecture fundamentals. Discuss concepts like event-driven architecture and CQRS patterns, and be ready to explain how you would apply these in real-world scenarios.