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For Companies At a Glance
- Tasks: Build and evolve data systems for fixed income, ensuring accuracy and quality.
- Company: Product-led fintech in capital markets with a focus on innovation.
- Benefits: Fully remote work, flexible hours, and a flat structure for direct access to decision-makers.
- Why this job: Own critical data pipelines and influence technical direction in a calm, focused environment.
- Qualifications: Experience in capital markets and building real data pipelines.
- Other info: Enjoy a supportive team culture with opportunities for meaningful impact.
The predicted salary is between 36000 - 60000 £ per year.
Overview
- Environment: Product-led fintech, capital markets
- Focus: Fixed income data infrastructure
- Location: Remote across the UK
- Stack: Python, SQL, Snowflake-style data platforms
- Team: Small, senior, low-ego
- Working style: High ownership, deep focus
Why you’d leave a good job for this one
If you enjoy working close to real market data, the kind that’s messy, delayed, corrected, and business-critical, this will resonate. You’ll own a meaningful part of a fixed income data platform that’s already live and now scaling. There’s no ticket queue and no hand-offs between “data”, “engineering”, and “product”. You’ll decide what matters, how it’s built, and when it’s ready to ship.
You’ll get:
- Ownership of core data pipelines, not just downstream analytics
- Time to think properly about data quality, lineage, and edge cases
- Direct influence over technical direction
- Long stretches of uninterrupted focus
- A calm pace that values judgement over urgency
This is engineering for people who care about how data behaves in production.
What you’ll spend your time doing
You’ll build and evolve the systems that ingest, normalise, and expose fixed income data. That includes:
- Designing and maintaining production data pipelines in Python
- Working closely with analysts to embed validation and fixes into the system
- Handling time-series and temporal data where accuracy matters
- Querying and modelling complex structured and semi-structured datasets
- Working with modern analytical data platforms (e.g. Snowflake-style environments)
- Using domain knowledge to shape how the product behaves, not just how it’s built
- Supporting ML and LLM-driven workflows where data quality is the limiting factor
This is hands-on, product-adjacent data engineering, not dashboard maintenance.
How the team builds
- Data & pipelines: Python, SQL
- Data platform: Cloud data warehouse and analytical tooling
- Infrastructure: Lean, pragmatic, minimal abstraction
- Tools: Linear and Slack
The focus is on correctness, observability, and systems that can be trusted.
This will suit you if…
- You’ve worked in capital markets and understand fixed income data behaviour
- You’ve built real data pipelines, not just reports or visualisations
- You’re comfortable owning systems end-to-end
- You enjoy working close to product and domain experts
You don’t need to know every bond instrument. You do need to understand why this data is hard and why it matters.
What you get in return
- Fully remote working across compatible time zones
- Flexible hours and time off
- Flat structure and direct access to decision-makers
- Trust to do your best work without micromanagement
- Optional in-person working if you’re UK-based
What happens next
If this sounds like the kind of work you want to be doing, start a confidential conversation. You’ll get real context, straight answers, and a clear sense of fit, before anything formal. No noise. No pressure. Just a grown-up discussion.
Fixed Income Data Engineer (Mid–Senior) – Remote First employer: Oceanredpartners
Contact Detail:
Oceanredpartners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Fixed Income Data Engineer (Mid–Senior) – Remote First
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech and capital markets space. Use LinkedIn to connect with current employees at companies you're interested in, and don't be shy about asking for informational chats. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Python and SQL. If you’ve worked with Snowflake or similar platforms, highlight that too. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss how you've handled messy data in the past and how you ensure data quality. Practice common data engineering interview questions to boost your confidence.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Make sure to tailor your application to highlight your experience with fixed income data and your ability to work closely with product teams. Let’s get you in for a chat!
We think you need these skills to ace Fixed Income Data Engineer (Mid–Senior) – Remote First
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Fixed Income Data Engineer role. Highlight your experience with Python, SQL, and any relevant data platforms to show us you’re a great fit!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re excited about this role and how your background in capital markets makes you the perfect candidate. Be genuine and let your personality shine through!
Showcase Your Projects: If you’ve worked on any relevant projects, especially those involving data pipelines or fixed income data, make sure to mention them. We love seeing real-world applications of your skills!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Oceanredpartners
✨Know Your Data Inside Out
Make sure you understand fixed income data behaviour and the challenges that come with it. Brush up on your knowledge of how data pipelines work, especially in Python and SQL, as this will be crucial for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled messy or complex data issues. Highlight your experience in building real data pipelines and how you ensured data quality and accuracy in production.
✨Familiarise Yourself with the Tech Stack
Get comfortable with Snowflake-style data platforms and any tools mentioned in the job description. Being able to speak confidently about your experience with these technologies will show that you're ready to hit the ground running.
✨Emphasise Ownership and Collaboration
This role values high ownership and collaboration with analysts. Be ready to discuss how you've taken charge of projects in the past and how you work closely with others to achieve common goals, especially in a remote setting.