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# Software Engineer Own The Data Platform Hedge Fund

- **Company:** Cto
- **Location:** London, UK
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** .NET Framework, Application Programming Interfaces (APIs), Airflow, C Sharp (Programming Language), Data Governance, Data Infrastructure, Extract Transform Load (ETL), Distributed Data Store, Monitoring of Systems, Meta-Data Management, Operational Databases, Redis, Software Engineering, SQL Databases, Data Streaming, Workflow Management Systems, Data Ingestion, Jupyter, Kubernetes, Storage Technologies, Cassandra, Apache Kafka, Docker
- **Published:** October 22, 2026
- **Apply:** https://www.reed.co.uk/jobs/software-engineer-own-the-data-platform-hedge-fund/57476441

## About the Role

Experience: 3-5 years in relevant data-focused engineering roles., 1. Demonstrated ownership of infrastructure systems, not just contribution to larger projects.

 2. Comfort discussing production data systems, SQL, data modelling, ETL and reliability at a technical level.
 3. Software engineering discipline: proper design, testing and maintainability.
 4. Willingness to operate across multiple technology areas, not just a narrow specialism.
 5. Genuine interest in being close to the business and understanding how technology drives investment outcomes.

Desirable but not required:

 1. Experience with orchestration tools (Airflow, Dagster, Prefect) or streaming platforms (Kafka, Azure Event Hubs).
 2. C# / .NET experience.
 3. Redis, Cassandra or distributed database knowledge.
 4. Container orchestration (Docker, Kubernetes).
 5. Jupyter and research-facing data tooling.
 6. Experience with financial market data, particularly fixed income and derivatives.

## Description

1. Take ownership of data ingestion, ETL pipelines and vendor dataset management.
 2. Design and evolve storage architecture, schemas and metadata management.
 3. Establish data quality frameworks and monitoring/observability systems.
 4. Ensure reliability and performance of critical data flows.
 5. Make data accessible to research teams, traders and other systems (APIs, notebooks, self-service tooling).
 6. Get involved in adjacent engineering problems (core systems, APIs, research infrastructure) as priorities shift.
 7. Partner directly with the CTO and investment team to understand business needs.