Snowflake & Data Engineering
Collaborate on the design of data contracts and semantic layer definitions to provide consistent, trusted metrics to downstream consumers.
DevOps, Quality & Collaboration
Champion CI/CD best practices for both application and data code, maintaining robust automated test coverage (unit, integration, and end-to-end).
Participate actively in Agile ceremonies, contribute to sprint planning, and drive engineering excellence through code reviews, pair programming, and technical documentation.
Monitor production systems, triage incidents, and perform root-cause analysis, ensuring high availability and SLA compliance across data product services.
Mentor junior engineers and contribute to the team's technical knowledge base through design documents, runbooks, and internal tech talks.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, or a related technical discipline.
4–8 years of professional experience in software engineering, with at least 2 years directly involving data platform or data product development.
Demonstrated track record of delivering production-grade, full-stack applications with measurable business impact.
Proficiency in advanced SQL (window functions, CTEs, recursive queries, QUALIFY) and Snowflake-specific DDL/DML including Time Travel, Zero-Copy Cloning, and Streams & Tasks.
Solid understanding of Snowflake's multi-cluster architecture, virtual warehouse sizing/scaling policies, query profiling, and cost governance via resource monitors.
Front-End: Strong proficiency in React.js (with hooks and context) or Vue.js, TypeScript, and a working knowledge of state management libraries (Redux / Pinia / Zustand).
Back-End: Hands-on experience building production APIs with Python (FastAPI / Flask / Django REST Framework) or Node.js (Express / NestJS).
Databases: Working knowledge of relational databases (PostgreSQL, MySQL) alongside Snowflake, including schema design, query optimization, and ORM usage.
Cloud Platforms: Practical exposure to AWS, Azure, or GCP services (e.g., S3/ADLS/GCS, Lambda/Functions, ECS/AKS/GKE) in the context of data workloads.
Infrastructure & Tooling: Experience with Docker, Kubernetes basics, Terraform or similar IaC tools, and standard CI/CD platforms (GitHub Actions, GitLab CI, Jenkins).
Fluent English is a must
Preferred Qualifications
Snowflake Cortex AI / ML functions
Data mesh or data product design patterns
Snowflake SnowCD / native app framework
OpenAPI / AsyncAPI specification design
GraphQL Federation / Apollo Studio
Observability (Datadog, OpenTelemetry, Prometheus)
Certification: Snowflake SnowPro Core or Advanced
Experience with data lakehouse architectures (Iceberg / Delta Lake)