Senior Software Engineer - Python / AWS

Qh4 Consulting; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Qh4 Consulting is recruiting for a Senior Python Engineer in London to join its investment technology team. You will design Python services, APIs and data pipelines supporting portfolio analytics and trading workflows.

The role focuses on cloud-native AWS development, CI/CD ownership, and close collaboration with portfolio managers and researchers. Hybrid work with 4 days in office, permanent employment, adaptable to growth in a global asset manager.

Qualifications

• 3+ years of hands‑on software or data engineering experience in financial services, ideally asset management.
• Strong Python development experience (3+ years) including APIs and data processing.
• Experience with cloud native AWS DevOps, CI/CD, testing and containerised deployments.
• Solid data engineering fundamentals: data modelling, pipelines, error handling, validation and lineage.
• Experience with event‑driven architectures and Kafka.
• Proficiency in SQL across PostgreSQL, SQL Server and Snowflake, with performance tuning and ETL.

Responsibilities

• Designing and building Python services, APIs and microservices for portfolio analytics and data processing.
• Writing, tuning and optimising complex SQL and ETL on PostgreSQL and SQL Server.
• Delivering scalable, event‑driven components using Kafka and asynchronous processing.
• Developing cloud‑native applications on AWS (Lambda, ECS/EKS, S3, Step Functions, Aurora).
• Owning CI/CD pipelines, automated testing and release processes for reliable deployments.
• Partnering with portfolio managers and quantitative researchers to translate requirements into production solutions.
• Championing AI‑assisted development and setting standards for reviewing AI‑generated code.

Skills

Python

AWS

DevOps

SQL

Kafka

ETL

Data engineering

Tools

PostgreSQL

SQL Server

Snowflake

Kafka

AWS

Lambda

ECS/EKS

S3

Step Functions

Job description

Senior Python Engineer – Investment Technology (AWS / DevOps)

London | Hybrid, 4 days in office | Permanent

Qh4 Consulting is recruiting on behalf of a leading global asset manager for a Senior Engineer to join its investment technology team in London, supporting the firm's investment business.

The team's platforms support the full investment process, from portfolio construction and trading through to analytics and operations, across equities, fixed income and alternatives. Its users include portfolio managers, quantitative researchers and analysts, as well as client-facing colleagues.

This is a hands‑on role covering both core technology platforms and tools developed in partnership with the investment teams. It involves evolving the platform architecture, improving the robustness of its data pipelines and raising engineering standards, working closely with colleagues in other regions. The role reports to the Director of Investment Technology.

Key responsibilities

• Designing and building Python services, APIs and microservices that support portfolio analytics, optimisation and data processing
• Writing, tuning and optimising complex SQL and high-volume ETL processes on PostgreSQL and SQL Server
• Delivering scalable, event‑driven components using Kafka and asynchronous processing
• Developing cloud‑native applications on AWS, including Lambda, ECS/EKS, S3, Step Functions and Aurora
• Owning CI/CD pipelines, automated testing and release processes so that deployments are consistent and dependable
• Partnering with portfolio managers and quantitative researchers to turn investment, risk and analytics requirements into production‑ready solutions
• Championing everyday use of AI‑assisted development across the team, and setting clear standards for reviewing AI‑generated code
• A background in financial services, ideally asset management, with 3+ years of hands‑on software or data engineering experience
• Strong, hands‑on Python development (3+ years), including APIs, data processing and service‑oriented design
• Practical DevOps experience on AWS, including CI/CD, automated testing and containerised, cloud‑native deployments
• 3+ years of SQL across PostgreSQL, SQL Server and/or Snowflake, including performance tuning and ETL
• A solid grasp of data engineering fundamentals: data modelling, pipeline design, error handling, validation and lineage
• Working knowledge of event‑driven and distributed architectures, for example using Kafka