Onix Datametica is Looking For Snowfalke Gcp Lead

Job Title: Snowflake Lead / Lead Snowflake Data Engineer

Summary

Snowflake Lead

Key Responsibilities

Technical Leadership

• Lead the end-to-end architecture, design, and implementation of Snowflake-based data solutions.
  
• Define best practices for Snowflake development, ELT patterns, security, CI/CD, and performance optimization.
  
• Provide technical guidance to data engineers and BI developers.
  

Data Engineering & Development

• Design and implement scalable data models (3NF, dimensional modeling, Data Vault).
  
• Build and optimize Snowflake objects: warehouses, schemas, tables, streams, tasks, snowpipes, UDFs.
  
• Develop and maintain ELT/ETL pipelines using tools such as

  DBT, Airflow, Matillion, Informatica, ADF

  , or equivalent.
• Implement data ingestion frameworks using cloud storage (S3/GCS/ADLS) and integration technologies (Kafka, APIs).
  

Performance & Optimization

• Optimize warehouse sizing, query performance, micro-partitioning, clustering, caching, and cost management.
  
• Monitor and fine-tune workloads to ensure high reliability and efficiency.
  

Security & Governance

• Implement Snowflake security best practices including RBAC, data masking, encryption, and access policies.
  
• Collaborate with data governance teams on metadata, cataloging, lineage, and quality frameworks.
  

Collaboration & Delivery

• Work closely with data science, analytics, and application teams to deliver high-quality datasets.
  
• Participate in sprint planning, solution reviews, and documentation.
  
• Communicate complex technical concepts to non-technical stakeholders.
  

Required Skills & Qualifications

• 712+ years of experience in data engineering, with at least

  3–5 years hands-on Snowflake

  .
• Strong SQL engineering background and expert-level Snowflake SQL understanding.
  
• Experienced in designing and implementing large-scale cloud data architectures.
  
• Strong proficiency with at least one cloud platform:

  AWS, Azure, or GCP

  .
• Hands-on experience with data orchestration and transformation tools (

  DBT, Airflow, ADF, Matillion, etc.

  ).
• Solid understanding of data modeling, warehousing concepts, and modern data architecture.
  
• Experience with version control, CI/CD pipelines, and DevOps practices.
  
• Knowledge of Python/Scala/Java for data pipeline development is a plus.
  
• Experience with data security, governance, and compliance frameworks.