About this role
You will take on the following responsibilities:
- Investigate and remediate production alerts using incident-specific runbooks, owning each issue through to resolution or escalation
- Author and improve runbooks, applying existing data-management workflow standards, turning recurring, ad-hoc fixes into clear, unambiguous, repeatable procedures that lower operational risk and increase throughput
- Mine our data to surface patterns and help root-cause issues, validate data, and reveal trends across large volumes
- Apply predefined acceptance and quality criteria to guarantee the integrity of financial data sets
- Collaborate with business partners, software engineers, data analysts, and other data operations specialists to understand and improve business processes
- Recommend and improve data-management policies and procedures to improve efficiency and accuracy
You should possess the following qualifications:
- Comfort with 'low-level' technology. You can work behind the UI: the UNIX/Linux command line, querying databases (SQL) to mine and validate data, reading logs, and navigating file systems, schedulers, and storage
- Exposure to scripting – Bash, Python, or a similar language – and the judgment to know when a script helps and when a runbook is the right answer
- A genuine pull toward operations: you like to execute daily, at volume, follow workflows to the letter, and feel the immediate impact of work done right
- Comfort switching between systems and tools – Linux/Windows, database/file-server, UI/command-line, text/numbers – without being dependent on a single framework
- Strong attention to detail and exceptional verbal and written communication
- BS in a technical discipline or equivalent hands-on experience in a comparable operational or technical role
- Minimum 1 year of experience required; 1-5 years of experience preferred
Preferred experience:
- Professional experience in data operations, technical operations, or a similar discipline – e.g. data operations analyst, systems/support engineer, data analyst, process engineer, systems administration, QA, or a structured operational background such as defense analysis, logistics, or maintenance technician work where you followed and built step-by-step procedures and worked with data and tooling
- Hands-on experience performing data-management and data-quality tasks in data-intensive environments
- A desire to grow your knowledge of finance and trading
Hours notice:
- This is a Tokyo-hours operational role within a global team that supports trading 24/5 across Houston, Tokyo, and London. Support is interrupt-driven and time-sensitive.