Requirements

2+ years in a data engineering, data science, or production-support role, or a degree in a technical or data discipline
Demonstrated experience with Python (or a comparable language)
Experience with at least one SQL variant (PostgreSQL, MSSQL, MySQL), and the ability to pick up others as needed
Strong analytical and troubleshooting skills; detail-oriented, self-motivated, and curious
Willingness to work shifts: the team works an alternating weekday early/late shift rotation, with participation in an on-call rota
Exposure to change-management and incident-management practices
Comfort with technical documentation and handling support cases
Comfortable working in both Windows and Linux environments

What You'll Be Doing

Engineer - Build and maintain the tooling that brings new data sources onto the platform, turning ad-hoc data handling into dependable, automated workflows in Python
Analyse - Get to know the data inside out, validate and reconcile it against expectations, and help researchers get it into the shape their models need
Investigate - When a derived dataset looks wrong, chase the discrepancy upstream until you find the root cause, combining detective work, technical analysis, and the right conversations across teams
Support - Provide proactive oversight of trading-critical scheduled jobs and Python pipelines, keeping them on time and within SLA; triage, troubleshoot, and resolve incidents under tight turnaround, validating downstream impact and keeping recovery procedures ready
Release - Own safe delivery to production - review configuration and code changes, enforce safe deployment standards, and coordinate risk-aware releases through GitLab and Octopus Deploy