Data Engineer - Tooling
We're looking for a hands-on Data Engineer to join QRT. In this role you'll build out the tooling that manages and monitors production datasets, keeping them flowing, observable, and reliable. You'll work closely with other engineering teams and business stakeholders to deliver a mission-critical platform.
- Data Quality Tools
Your key deliverable is to develop and maintain a platform which ensures the quality of our data-pipelines, and alerts stakeholders to critical production issues. - Library Maintenance
Maintain and improve shared libraries which are used by developers across the data-function and facilitate the rapid onboarding of new datasets. - Cross-team Integrations
Design, build, and document our integrations with other team's processes, which alert them to relevant issues with our data-pipelines. - Observability & Monitoring
Build out the observability stack (logs, metrics, tracing) to monitor our data assurance system, as well as other tools for the management of our data-pipeline lifecycle. - Platform Support
Support users in best practice usage of our tooling, migrate code to the latest standards as well as investigate, debug and resolve issues with our platform.
You thrive at the intersection of software engineering, data operations, and DevOps. You're comfortable both architecting solutions and writing the code to deploy and maintain them, and you relish collaborating with diverse stakeholders to turn requirements into production-grade systems.
- 5+ years of hands-on experience in data engineering or data-adjacent engineering roles
- Strong software engineering fundamentals and proficiency in Python
- Experience with workflow orchestration frameworks (e.g. Argo, Celery, Airflow)
- Experience designing and implementing RESTful APIs and internal service integrations
- Experience with observability tools (e.g. Prometheus, Grafana, CloudWatch)
- Familiarity with Kubernetes, container orchestration, and cloud infrastructure (AWS preferred)
- Exposure to the front-end, particularly with regards to custom monitoring dashboards, is a plus
- Knowledge of data-quality frameworks (Soda/Great Expectations) is a plus
- Knowledge of ETL/ELT pipelines, and metadata management is a plus
- Excellent communication skills and a collaborative mindset to work effectively with other engineers, quants and traders
- Self-starter mentality with the ability to work autonomously within a globally distributed team
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