Software Development Engineer - Data

Software Development Engineer - Data

Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
Square Point Capital

At a Glance

  • Tasks: Ensure the performance and stability of our data ecosystem while automating workflows.
  • Company: Join a leading tech firm focused on innovation and reliability.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on collaboration and career advancement.
  • Why this job: Make a real impact by enhancing data systems and driving automation.
  • Qualifications: Bachelor's degree in Computer Science and 4+ years in Software Engineering.

The predicted salary is between 63000 - 77000 Β£ per year.

As a Reliability Software Engineer in the Data team, you will play a critical role in ensuring the performance, stability, and availability of Squarepoint's data ecosystem. The team's mandate spans maintaining critical data pipelines, automating operational workflows, managing infrastructure, and building tools focused on observability, regression prevention, and self-serve automation. The team also serves as a key operational hub within Data Development, handling everything from incident triage to active resolution, making this a high-responsibility role that demands strong engineering skills, sharp analytical thinking, and a deep sense of ownership.

Responsibilities

  • Core Responsibilities
    • Automation Systems: Build and improve automation that streamlines operational tasks and workflows
    • Infrastructure Management: Keep Data Development infrastructure healthy via monitoring, observability, and maintenance
    • Reliability Engineering: Own deployments, support users, lead incident resolution, and plan capacity/performance
    • Data Pipelines: Build and monitor production pipelines, onboarding data trials and loading Timeseries for research and trading
  • Operations Responsibilities
    • Incident Management: Perform root cause analyses and drive remedial actions
    • Day-to-Day Operations: Handle production deployments, config changes, and user requests
  • Key Engineering Initiatives
    • Observability: Health monitoring platform with configurable monitors and custom checks
    • Deployment Automation: Platform for scheduling, orchestrating, and validating safe production rollouts
    • Self-Serve Automation: Jira-driven platform that applies operational changes after approvals

Required Qualifications

  • Education: Bachelor's degree in Computer Science, Engineering, or a related subject
  • Experience: 4+ years of proven experience in Software Engineering, Software Reliability, or a similar role
  • Python: Two or more years of hands-on experience programming in Python
  • Linux: Proficiency with the Linux command line
  • Databases: Knowledge of relational databases, primarily PostgreSQL
  • Tools: Familiarity with Git, Consul, Grafana, Kibana, and cloud platforms such as Google Cloud or AWS
  • Communication: Excellent verbal and written skills for working effectively within a global team
  • Mindset: Proactive, detail-oriented, and self-driven with a strong sense of ownership and accountability

Software Development Engineer - Data employer: Square Point Capital

Squarepoint is an exceptional employer that fosters a dynamic work culture where innovation and collaboration thrive. As a Software Developer in the Data Reliability team, you will benefit from a supportive environment that prioritises employee growth through continuous learning opportunities and hands-on experience with cutting-edge technologies. Located in a vibrant city, Squarepoint offers unique advantages such as flexible working arrangements and a strong emphasis on work-life balance, making it an ideal place for those seeking meaningful and rewarding employment.

Square Point Capital

Contact Details:

Square Point Capital Recruitment Team

We think you need these skills to ace Software Development Engineer - Data

Automation Systems
Infrastructure Management
Reliability Engineering
Data Pipelines
Incident Management
Observability
Deployment Automation