Lead Snowflake Data Engineer

Responsibilities

• Design and implement scalable Snowflake data models tailored for data ingestion and analytics requirements

• Build and maintain robust ETL pipelines to integrate data from multiple sources into Snowflake, ensuring data integrity and consistency

• Optimize Snowflake usage and storage, tuning query performance and managing data partitions for reliable data access

• Implement best practices in data security, role-based access control and data masking within Snowflake to uphold compliance and governance standards

• Utilize DBT and workflow management tools such as Apache Airflow to schedule data processing and automate pipeline monitoring

• Partner with data scientists, business analysts and other stakeholders to address complex data challenges and troubleshoot Snowflake-related issues

• Develop comprehensive documentation for data structures, ETL workflows and system processes to promote transparency and knowledge sharing within the team

Requirements

• 8 to 13 years of working experience in data engineering or related fields

• Knowledge of Snowflake, DBT and either AWS or Azure

• Proficiency in Python programming

• Skills in workflow management tools such as Argo, Oozie or Airflow

• Expertise in Snowflake modeling including roles, schema and databases

• Background in data modeling, particularly Data Vault methodology

• Capability to design and develop data transformation pipelines using the DBT framework

• Understanding of scalable, secure and high-performance data warehouse architectures

  • Familiarity with integrating monitoring and observability capabilities into data platforms