Senior Full-Stack Engineer (Java & Python)

McCabe & Barton; Greater London; On-site; GBP 75,000 - 100,000; Full time

Job summary

A leading investment house is seeking a high-impact Senior Full-Stack Engineer to join its growing technology team. This role involves designing and maintaining robust data pipelines, ensuring data quality, and collaborating with stakeholders to drive strategic tech solutions. Ideal candidates have 5+ years in data/software engineering with strong full-stack skills in Python, Java, and React, along with experience in modern data engineering tools like Airflow and Snowflake. Competitive compensation and opportunities for growth are offered.

Qualifications

• 5+ years' experience in data or software engineering within financial services or regulated industry.
• Strong full-stack experience with Python, Java (Spring Boot), and React.
• Hands-on experience with data engineering tools like Airflow, Spark, Kafka, and Snowflake.
• Experience with cloud platforms, containerisation, and CI/CD pipelines.
• Solid understanding of data governance and compliance.

Responsibilities

• Design, build, and maintain scalable data pipelines for analytics.
• Ensure data quality and governance through modern practices.
• Own and evolve data models and integrations across platforms.
• Deliver data analysis and visualisation to support business objectives.
• Lead incident investigation and root-cause analysis.

Skills

Full-Stack Experience

Python

Java (Spring Boot)

React

SQL

Data Engineering Tools

Cloud Platforms

Containerisation (Docker/Kubernetes)

CI/CD Pipelines

Automated Testing

Excellent Communication Skills

Agile Collaboration

Tools

Airflow

Spark

Kafka

dbt

Snowflake

Terraform

Prometheus

Grafana

ELK

Job description

Overview

Senior Full-Stack Engineer

We are seeking a high-impact Senior Full-Stack Engineer to join a growing technology team for a leading investment house supporting market data services within a regulated, enterprise environment.

This role sits at the intersection of data engineering, full-stack development, and business engagement, working closely with stakeholders and external vendors to design and deliver robust, scalable technology solutions aligned to a strategic roadmap.

What you'll do

• Design, build, and maintain reliable, scalable data pipelines supporting complex analytical and sustainability data workloads.
• Ensure data quality, governance, and robustness through modern data engineering practices, automated validation, monitoring, and testing.
• Own and evolve data models and system integrations across multiple platforms and third-party services.
• Deliver data analysis, reporting, and visualisation to support business and technology objectives.
• Lead incident investigation and root-cause analysis for data-related issues, driving continuous improvement.
• Collaborate with enterprise data teams to contribute to data architecture and governance.
• Act as a bridge between technical and non-technical stakeholders, clearly communicating progress, risks, and requirements.
• Contribute to the future data roadmap, including the adoption of AI and emerging data technologies.

What we're looking for

• MUST have 5+ years' experience in data or software engineering within financial services or a similar regulated industry.
• Strong full-stack experience with Python, Java (Spring Boot), React, SQL, and relational databases.
• Hands-on experience with modern data engineering tools (eg Airflow, Spark, Kafka, dbt, Snowflake or similar).
• Experience with cloud platforms, containerisation (Docker/Kubernetes), and CI/CD pipelines.
• Solid understanding of data governance, validation, and compliance.
• A strong advocate for automated testing, observability, and engineering best practice.
• Excellent communication skills and the ability to collaborate in agile, cross-functional teams.

Desirable

• Experience with infrastructure as code (Terraform, Helm).
• Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK).
• Exposure to regulated environments and associated data controls.