Related skills
azure docker aws python kubernetes📋 Description
- Lead design and implementation of data and AI/ML architectures across cloud and on-premise.
- Lead complex engagements, providing strategic technical vision aligned with business goals.
- Build strong relationships with key stakeholders, acting as trusted technical advisor.
- Lead technical workshops, training sessions, and presentations.
- Define and execute data lifecycle: ingestion, storage, processing, visualization.
- Ensure solutions adhere to security, compliance, and architecture frameworks.
🎯 Requirements
- 7+ years of experience in solutions architecture, with Big Data and cloud platforms (AWS, GCP, Azure).
- Excellent communication and problem-solving skills, able to explain concepts to technical and non-technical audiences.
- Proficiency in data engineering and analytics, designing data pipelines using AWS/GCP/Azure data stacks.
- Strong AI/ML concepts understanding and experience integrating AI/ML components.
- Proven experience with data lakes, data warehouses, and real-time analytics.
- Hands-on with Kubernetes, Docker, and containerized applications.
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