Data Reliability Engineer at Susquehanna International Group, LLP (SIG)

Dublin, Leinster, Ireland -

Full Time

Start Date

Immediate

Expiry Date

16 May, 26

Salary

0.0

Posted On

15 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Airflow, Troubleshooting, Monitoring, Alerting, Automation, Gitlab, Octopus Deploy, Change Management, Incident Management, Data Pipelines, Release Management, Quantitative Research, Machine Learning

Industry

Financial Services

Description

Overview Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together. We’re looking for a Data Reliability Engineer to help keep our trading and data platforms running seamlessly. In this role, you’ll be the guardian of our data pipelines — ensuring that trading critical Airflow workflows and Python-based jobs run smoothly, on time, and with precision. You’ll dive deep into incidents when they happen, diagnose issues quickly, and make the fixes that keep downstream systems healthy and reliable. Your work will directly support the speed and stability our trading teams depend on every day. You’ll collaborate closely with quantitative researchers, data and reliability engineers, and developers to review changes, manage releases, and strengthen our overall deployment practices. Beyond keeping things running, you’ll help make them better — improving monitoring, alerts, and recovery processes while automating wherever possible. This role is perfect for someone who thrives on ownership, loves solving complex operational puzzles, and is passionate about building robust, high-performance data systems that never miss a beat. In this role you will: Ensure Platform Reliability - Monitor and maintain trading-critical Airflow DAGs and Python-based pipelines, ensuring jobs run on time and within SLAs Incident Response & Recovery - Triage, troubleshoot, and resolve failures quickly; validate downstream impacts and maintain tested rollback/recovery procedures Change & Release Management - Act as a release gatekeeper—review code/config changes, enforce safe deployment standards, and coordinate risk-aware releases via Git(lab) and Octopus Deploy Collaboration & Communication - Partner with quants and engineers to assess change impacts, document runbooks, and communicate operational updates and risks Continuous Improvement - Enhance monitoring, alerting, and automation; track KPIs and drive initiatives that strengthen platform resilience and reduce incident recurrence What we're looking for Degree in a technical or business discipline or equivalent industry experience of 1+ years Demonstrated experience with Python or equivalent language Excellent analytical & troubleshooting skills, self-motivated and curious Willing to work shift hours, to cover early and late responsibilities (alternating) Experience with Change Management, Incident Management Procedures Experience of technical documentation & support cases Desirable Financial Trade Floor experience is a plus but not essential, training will be provided. Knowledge of system monitoring tools such as Check_MK, Splunk, ELK Awareness of modern distributed application systems and the glue that binds them - messaging and database systems If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee. #LI-ED1

Responsibilities

The Data Reliability Engineer will monitor and maintain trading-critical Airflow DAGs and Python-based pipelines, ensuring timely execution and SLA adherence. Responsibilities also include rapid incident response, troubleshooting failures, validating downstream impacts, and managing safe deployment practices.