Responsibilities
- Manage full lifecycle data workflows, from gathering requirements and designing architecture to deployment and ongoing operations, covering data ingestion, validation standards, and integration with data science initiatives.
- Develop scalable batch and real-time data processing pipelines and lakehouse architectures designed for high-volume data handling.
- Investigate and implement emerging technologies to expand the data platform’s capacity in response to accelerating data growth.
- Work closely with data science teams to operationalize machine learning and artificial intelligence models within product environments.
- Coordinate with cloud, DevOps, software development, and client-facing teams to build secure, reliable, and scalable data solutions that address key business challenges.
- Assess and integrate new data technologies and architectural patterns to advance the data ecosystem as demands increase in scale and complexity.
Work Arrangement
Hybrid
Other
- Flexible working environment
- Volunteer time off
- LinkedIn Learning
- Employee-Assistance-Program (EAP)
