Snowflake Data Engineer

LTM Inc

$110K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in data engineering with a strong focus on Snowflake
  • Proficiency in Python for data manipulation and automation
  • Hands-on experience with DBT for data transformations
  • Solid understanding of ETL/ELT processes and frameworks
  • Experience in data modeling and warehouse architecture design

Responsibilities

  • Design and implement scalable ETL/ELT data pipelines
  • Develop and maintain Snowflake data models and architecture
  • Manage DBT models for transformation and tracking
  • Write Python scripts for data ingestion and automation
  • Collaborate with stakeholders to gather and clarify data needs
  • Ensure data governance and quality across platforms
  • Optimize performance of data pipelines and queries

Benefits

  • Flexible remote work environment
  • Opportunity to work with cutting-edge data technologies
  • Collaborative team dynamics with cross-functional colleagues
  • Focus on best practices in data engineering and career growth
Full Job Description
Role description

Snowflake Data Engineer

Location Remote

We are looking for a highly skilled Data Engineer with handson experience in Snowflake Python DBT and modern data architecture The ideal candidate will be responsible for designing building and maintaining scalable data pipelines and data warehouse solutions that support analytics and business intelligence initiatives

Key Responsibilities

Design and implement scalable data pipelines using ETLELT frameworks

Develop and maintain data models and data warehouse architecture using Snowflake

Build and manage DBT Data Build Tool models for data transformation and lineage tracking

Write efficient and reusable Python scripts for data ingestion transformation and automation

Collaborate with data analysts data scientists and business stakeholders to understand data requirements

Ensure data quality integrity and governance across all data platforms

Monitor and optimize performance of data pipelines and queries

Implement best practices for data engineering including version control testing and CICD

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