Senior Data Engineer

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.

• Essential Skills/ExperienceA 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.