Senior Python Data Engineer - Python, AI, Pre-Trade, Market Data - Cadogan Solutions

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., 1. Design, develop, and maintain Python-based data engineering solutions supporting strategic data platforms

2. Build scalable ETL and data ingestion pipelines processing large volumes of market, reference, and business data
3. Develop data transformation, validation, reconciliation, and quality control frameworks
4. Engineer solutions that improve the accessibility, governance, and usability of enterprise data assets
5. Build APIs, automation tooling, and workflow orchestration capabilities to support data distribution and operational processes
6. Partner with business, operations, and technology stakeholders to understand data requirements and deliver scalable solutions
7. Contribute to modern cloud-based data platform initiatives across AWS, Azure, and related technologies
8. Support the onboarding of new data sources and vendor feeds into strategic enterprise platforms
9. Improve observability, monitoring, lineage, and operational controls across data workflows
10. Participate in architecture discussions and help shape future-state data platform capabilities

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., 1. Strong commercial experience developing in Python

2. Experience building enterprise-scale data engineering solutions
3. Experience designing and supporting ETL/ELT pipelines
4. Experience working with large and complex datasets
5. Strong understanding of data quality, validation, reconciliation, and operational controls
6. Experience working within financial services, investment banking, capital markets, or asset management environments
7. Ability to work directly with business stakeholders and translate requirements into technical solutions

Desirable Experience

1. Market data, reference data, or trading data experience
2. Cloud platforms including AWS, Azure, or GCP
3. Spark, Databricks, Snowflake, Airflow, DBT, or similar modern data technologies
4. API development and event-driven architectures
5. Data governance, metadata management, and data lineage tooling
6. Experience supporting front-office or investment management functions
7. Knowledge of entitlement, access control, or data permissioning workflows