Solutions Engineer _Python,Snowflack,Java

We are seeking a hands-on Senior Solution Engineer to design, build, and operate robust cloud-native data and AI solutions. The ideal candidate combines strong software engineering fundamentals with deep practical experience in AWS and Snowflake Responsibilities Design & Build Solutions : Deliver production-grade software and data solutions end-to-end, from architecture to deployment and continuous improvement.

Data Engineering : Implement scalable, secure, and well-governed data pipelines across structured, semi-structured, and unstructured sources.

Snowflake Optimization : Model, curate, and optimize datasets, schemas, and structures for performance and usability.

Software Engineering Practices : Apply clean code, modular design, automated testing, CI/CD, observability, and secure development.

Stakeholder Collaboration : Translate requirements into robust solutions and enable advanced analytics and AI use cases.

AI-Assisted Development : Use tools like GitHub Copilot, Claude, or Cursor to accelerate coding, testing, and documentation.

Cloud-Native Integrations : Build integrations and automation using AWS compute, storage, networking, and managed AI services.

Operations Ownership : Manage deployment, release, monitoring, troubleshooting, and incident resolution.

Required 7+ years of professional experience in software, solution, or data engineering roles.

Proven track record of delivering production-grade systems in enterprise environments.

Deep hands-on AWS experience (compute, storage, networking, IAM, security, orchestration, monitoring, serverless/event-driven architectures).

Deep hands-on Snowflake experience (data modeling, SQL tuning, pipeline integration, governance, cost/performance optimization).

Strong proficiency in Python and/or Java with solid software design principles.

Familiarity with AWS AI services (e.g., Amazon Bedrock) and agent-based AI solution patterns.

Experience with AI-assisted engineering tools (Copilot, Claude, Cursor, etc.).

Knowledge of CI/CD, infrastructure-as-code, DevOps practices, and production support .

Ability to translate ambiguous business problems into clear technical scopes and measurable success criteria.