
Data Engineer
3 weeks ago
Responsibilities:
- 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.
Experience:
- 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
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