Snowflake, Python

Snowflake, Python

Technology->Data on Cloud-DataStore->Snowflake Technology->->Python Preferred Qualifications: • Experience leading architecture for enterprise-scale Snowflake implementations, including multi-environment setup and workload isolation strategies. • Strong experience with Python data engineering ecosystems (e.g., Pandas, PySpark) and building reusable frameworks/utilities. • Expertise in orchestration and scheduling patterns for data workflows, including dependency management and monitoring. • Experience implementing data quality checks, automated testing strategies, and observability for pipelines and datasets. • Familiarity with CI/CD practices for data platforms, including version control, automated deployments, and environment promotion. • Strong stakeholder management skills with the ability to communicate trade-offs, influence decisions, and align teams on technical direction. Key Responsibilities: • Lead end-to-end design and implementation of Snowflake-based data warehouse/lakehouse solutions aligned to business and analytics needs. • Architect and optimize data models (dimensional, normalized, and hybrid) to support reporting, BI, and advanced analytics use cases. • Develop and maintain Python-based data processing components, utilities, and orchestration logic to enable scalable data workflows. • Build and optimize Snowflake objects including databases, schemas, tables, views, stages, file formats, tasks, streams, and stored procedures where applicable. • Drive performance tuning across Snowflake (warehouse sizing, clustering, caching, query optimization) and Python workloads to meet SLAs. • Establish and enforce data engineering standards for code quality, testing, documentation, and release management. • Implement secure data access patterns, role-based access control, and governance practices to ensure compliance and auditability. • Collaborate with stakeholders to translate requirements into technical designs, delivery plans, and measurable outcomes. • Mentor team members through design reviews, pair programming, and technical guidance; lead troubleshooting and root-cause analysis for production issues. • Coordinate with cross-functional teams to manage dependencies, risks, and delivery timelines for multiple concurrent initiatives. Minimum Qualifications: • Bachelor’s or Master’s degree (BTECH, MTECH, MCA, MSC) in Computer Science, Engineering, or a related field. • 8–12 years of overall experience with strong ownership in data engineering and platform delivery. • 8+ years of hands-on experience with Snowflake, including data modeling, performance optimization, and production support. • 8+ years of strong Python development experience for data engineering use cases (data processing, automation, and integration). • Proven ability to lead technical design discussions, perform code reviews, and guide engineering best practices. • Strong SQL skills and experience building reliable, maintainable data pipelines and datasets for analytics consumption.