At a Glance
- Tasks: Design and build scalable data solutions using Python for trading and market data.
- Company: Join a Tier 1 Financial Institution with a focus on innovation.
- Benefits: Competitive salary, career growth, and exposure to cutting-edge technologies.
- Other info: Dynamic environment with opportunities to work on cloud-based data platforms.
- Why this job: Make a real impact in a high-visibility programme within the financial sector.
- Qualifications: Strong Python skills and experience with ETL pipelines in financial services.
The predicted salary is between 70000 - 90000 £ per year.
A Tier 1 Financial Institution is seeking a Python Data Engineer to join a strategic front-office data and technology function responsible for building and modernising enterprise data platforms supporting trading, market data, and business-critical workflows. This role sits at the intersection of data engineering, platform development, and enterprise data management. The successful candidate will help design and build scalable solutions that improve how data is onboarded, governed, distributed, and consumed across multiple business areas and asset classes. The environment is highly complex, operating across large-scale market data ecosystems, trading platforms, cloud-native infrastructure, and enterprise data services.
The team is looking for engineers who combine strong Python and data engineering expertise with a practical understanding of how enterprise data platforms operate within large financial institutions. Successful candidates will have experience solving complex data challenges, working across multiple stakeholder groups, and delivering scalable solutions that support critical business functions. This is a high-visibility programme with significant investment and long-term strategic importance across the organisation.
Responsibilities- Design, develop, and maintain Python-based data engineering solutions supporting strategic data platforms
- Build scalable ETL and data ingestion pipelines processing large volumes of market, reference, and business data
- Develop data transformation, validation, reconciliation, and quality control frameworks
- Engineer solutions that improve the accessibility, governance, and usability of enterprise data assets
- Build APIs, automation tooling, and workflow orchestration capabilities to support data distribution and operational processes
- Partner with business, operations, and technology stakeholders to understand data requirements and deliver scalable solutions
- Contribute to modern cloud-based data platform initiatives across AWS, Azure, and related technologies
- Support the onboarding of new data sources and vendor feeds into strategic enterprise platforms
- Improve observability, monitoring, lineage, and operational controls across data workflows
- Participate in architecture discussions and help shape future-state data platform capabilities
- Experience designing and supporting ETL/ELT pipelines
- Experience working with large and complex datasets
- Strong understanding of data quality, validation, reconciliation, and operational controls
- Experience working within financial services, investment banking, capital markets, or asset management environments
- Ability to work directly with business stakeholders and translate requirements into technical solutions
- Market data, reference data, or trading data experience
- Cloud platforms including AWS, Azure, or GCP
- Spark, Databricks, Snowflake, Airflow, DBT, or similar modern data technologies
- API development and event-driven architectures
- Data governance, metadata management, and data lineage tooling
- Experience supporting front-office or investment management functions
- Knowledge of entitlement, access control, or data permissioning workflows
Senior Data Engineer - Python, AI, Pre-Trade, Market Data employer: Cadogan Solutions
As a Senior Data Engineer at this Tier 1 Financial Institution, you will thrive in a dynamic and innovative work environment that prioritises employee growth and collaboration. The company offers competitive benefits, a strong focus on professional development, and the opportunity to work with cutting-edge technologies in a high-visibility role that directly impacts critical business functions. With a commitment to fostering a culture of excellence and inclusivity, this institution is an exceptional employer for those seeking meaningful and rewarding careers in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Python, AI, Pre-Trade, Market Data
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in data engineering. Building relationships can open doors that job applications alone can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your Python projects, ETL pipelines, or any cool data solutions you've built. This gives potential employers a taste of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and data engineering concepts. Practice common interview questions and be ready to discuss how you've tackled complex data challenges in the past.
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Engineer - Python, AI, Pre-Trade, Market Data
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Data Engineer. Highlight your Python skills and any experience with ETL pipelines, as well as your understanding of data governance and cloud platforms. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your experience can help us modernise our enterprise data platforms. Be specific about your achievements and how they relate to the job description.
Showcase Relevant Projects:If you've worked on projects involving large datasets or cloud technologies like AWS or Azure, make sure to mention them. We love seeing real-world applications of your skills, so don’t hold back on sharing your successes!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Cadogan Solutions
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially in relation to data engineering. Be prepared to discuss your experience with ETL/ELT pipelines and how you've tackled complex datasets in the past. Practising coding challenges can also help you feel more confident.
✨Understand the Financial Landscape
Familiarise yourself with the financial services sector, particularly investment banking and capital markets. Knowing how enterprise data platforms operate within these environments will give you an edge. Be ready to discuss how your previous experiences align with the needs of a Tier 1 financial institution.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've solved complex data challenges in your previous roles. Highlight your ability to work with multiple stakeholders and deliver scalable solutions. This will demonstrate your practical understanding of data governance and operational controls.
✨Get Comfortable with Cloud Technologies
Since the role involves cloud-based data platforms like AWS and Azure, make sure you're up to speed with these technologies. Be ready to discuss any relevant projects you've worked on and how you've contributed to modern data platform initiatives.
