Snowflake Lead Data Engineer

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. #J-18808-Ljbffr Anblicks