Senior Snowflake Data Engineer

Job Title: Senior snowflake Data Engineer Location: Dallas, TX Key Responsibilities • Lead the end-to-end architecture and implementation of Snowflake(Bronze/Silver/Gold layers). • Partner with business and data stakeholders to translate requirements into canonical models, ontologies, and data products. • Define and enforce data modeling standards, naming conventions, and domain-driven design principles. • Guide teams on data ingestion patterns, transformation frameworks (e.g., dbt), and performance optimization in Snowflake. • Integrate data management capabilities including Data Quality using SODA, Data Governance, Metadata Management, and Data Observability. • Ensure platform scalability, security, cost optimization, and compliance with enterprise standards. • Provide technical leadership and mentorship to data engineers and modelers. • Act as a key contributor in roadmap planning, technical decision-making, and stakeholder communication. Required Skills & Experience • 10+ years of experience in data engineering and platform architecture, with at least 3+ years in a lead role. • Strong hands-on experience with Snowflake (performance tuning, clustering, security, cost optimization). • Hands-on experience with cloud platforms (AWS, Azure, or GCP) • Understanding with Data Domains (Client, Finance etc.) • Deep understanding of data modeling (dimensional, canonical, domain-driven). • Experience designing or working with ontology / semantic layers (business vocabularies, relationships, metrics). • Strong knowledge of modern data stack tools (dbt, orchestration, CI/CD for data). • Experience implementing Data Quality, Data Governance, Metadata, and Data Observability solutions. • Experience with orchestration tools such as: Apache Airflow, Prefect, or Luigi. • Solid SQL skills and strong understanding of ELT patterns. • Ability to lead cross-functional teams and communicate complex concepts to both technical and non-technical stakeholders. Nice to Have • Experience with knowledge graphs, semantic models, or graph technologies. • Exposure to enterprise data platforms supporting multiple domains and global users. • Background in cloud-native architectures and large-scale data modernization programs.