Solutions Engineer _Python,Snowflack,Java
# Solutions Engineer _Python,Snowflack,Java **SPI GLOBAL CONTENT HOLDING PTE. LTD.** · Outram · `On-site` 🕒 **Статус:** *Опубликовано: 6 дней назад* · *Источник: Indeed* --- ### About the Role 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.
Наблюдалась 2026-09-21, впервые 2026-09-15, источник — Indeed.