Accountabilities
Architect of Solutions: Lead the design, development, and enhancement of scalable ML Ops/Data pipelines and Data Products on cloud-native platforms.
Technical Expertise: Demonstrate your expertise in Python, Pyspark, Docker, Kubernetes, and AWS ecosystems to deliver exceptional solutions.
Collaborative Spirit: Work hand-in-hand with global and diverse Agile teams, from data to design, to overcome technical data challenges.
Innovate & Inspire: Stay ahead of the curve by integrating the latest industry trends and innovations into your work such as GenAI.
Skills/Experience
- A proactive mindset and enthusiasm for Agile environments.
- Strong hands-on experience with cloud providers and services.
- Experience in performance tuning SQL and ML Ops data pipelines.
- Extensive experience in troubleshooting data issues, analyzing end-to-end data pipelines, and working with users in resolving issues.
- Masterful debugging and testing skills to ensure excellence in execution.
- Inspiring communication abilities that elevate team collaboration.
- Experience of structured, semi-structured (XML, JSON), and unstructured data handling including extraction and ingestion via web-scraping and FTP/SFTP.
- Production experience delivering CI/CD pipelines (Github, Jenkins, DataOps.Live).
- Cloud DevOps Engineer who can develop, test, and maintain CICD Pipeline using Terraform, cloud formation.
- Remain up to date with the latest technologies, like GenAI / AI platforms and FAIR scoring to improve outcomes.