Lead / Principal Snowflake Engineer

We are seeking a Lead / Principal Snowflake Engineer to architect and build scalable, enterprise-grade data platforms on Snowflake. This role will own the end-to-end data lifecycle, including ingestion, transformation, semantic layer implementation, and delivery of Front-end application.

You will act as a technical leader and architect, driving platform modernization, enforcing engineering standards, and ensuring performance, scalability, and cost efficiency., 1. Data Platform Architecture & Modernization

• Design and build scalable Snowflake data platforms using best practices
• Assess legacy systems and define modernization and migration strategies
• Establish architectural standards, governance frameworks, and reusable patterns

1. Data Engineering & Integration * Develop end-to-end ELT pipelines from APIs, databases, SaaS platforms, and event streams * Build reliable connectors with robust error handling, retry logic, and data consistency * Transform raw data into clean, normalized, consumption-ready datasets

2. Data Modeling & Semantic Layer * Design dimensional data models (fact/dimension, star/snowflake schemas) * Implement business-friendly semantic layers aligned with enterprise reporting needs * Build aggregations, pre-computed metrics, and optimized data structures for analytics

3. Snowflake Engineering & Optimization * Develop advanced SQL transformations and implement performance tuning strategies * Manage warehouse sizing, workload optimization, and cost governance * Implement RBAC, data security, versioning, and data sharing mechanisms

4. BI & Analytics Enablement * Align Snowflake data models with Power BI (DirectQuery and Import models) * Optimize datasets for performance, scalability, and reporting efficiency

5. Data Quality, Observability & AI Enablement * Implement data validation, monitoring, and alerting frameworks * Ensure high reliability and trust in downstream data consumption * Leverage Snowflake Cortex, Agentic AI patterns, and AI tools to automate workflows and improve engineering productivity

6. Leadership & Stakeholder Engagement * Provide technical leadership and mentor engineering teams * Collaborate with stakeholders to define business and technical requirements * Drive adoption of best practices in Snowflake and modern data engineering

• 10+ years of experience in data engineering, data architecture, or related roles
• Strong expertise in Snowflake (data modeling, performance tuning, governance, security)
• Proven experience building end-to-end data platforms from scratch
• Deep knowledge of semantic layer design and BI alignment
• Advanced SQL expertise (window functions, PIVOT, GROUPING SETS, etc.)
• Experience with multi-source data integration (RDBMS, APIs, SaaS, streaming)
• Strong cloud expertise (Azure/AWS) with Snowflake integration
• Proficiency in Python for data engineering and automation
• Familiarity with Agentic AI concepts and AI-driven tools to improve development efficiency and automation

Preferred Qualifications

• Experience with dbt (models, testing, lineage, documentation)
• Exposure to data observability tools (SODA.)
• Experience with SnapLogic, AWS S3, or equivalent services
• Experience with Snowflake Cortex / AI-based workflows
• Domain experience in Operation Data ( Cloud FinOps, AI Tool Ops, Managed Services Data, Agile Delivery Data will be Advantage.

Success Criteria

• Ability to design, architect, and deliver Snowflake platforms end-to-end
• Strong focus on performance, scalability, and cost optimization
• Expertise in data modeling and semantic layer implementation
• Demonstrated technical leadership and stakeholder management.