Lead / Principal Snowflake Engineer

Job Title: Lead / Principal Snowflake Engineer Location: Dallas, TX Role Overview 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. Key Responsibilities 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 1. 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 1. 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 1. BI & Analytics Enablement • Align Snowflake data models with Power BI (DirectQuery and Import models) • Optimize datasets for performance, scalability, and reporting efficiency 1. 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 1. 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 Required Qualifications • 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.