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Jr. Snowflake Data Engineer - DBT

Cliff Services IncJohnston, RI🇺🇸United StatesPosted 20 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Johnston, RI, United States
Posted
1 week ago
SQLETLSnowflakeData PipelineGitPythondbt

Job Description

Jr. Snowflake Data Engineer DBT
Location: Rhode Island (RI) Onsite
Openings: 7 Job Summary

We are looking for a Junior Snowflake Data Engineer with hands-on experience in Snowflake, DBT, SQL, and modern data engineering practices. The ideal candidate will work with the data engineering team to develop, maintain, and optimize data pipelines and transformation workflows supporting banking and financial data.

Key Responsibilities
  • Develop and maintain data transformation pipelines using Snowflake and DBT.
  • Write and optimize SQL queries for data extraction, transformation, and loading.
  • Build DBT models, tests, documentation, and reusable transformation logic.
  • Work with structured and semi-structured data within Snowflake.
  • Assist with data ingestion, integration, and ETL/ELT processes.
  • Perform data validation, reconciliation, and quality checks.
  • Troubleshoot data pipeline and transformation issues.
  • Collaborate with senior data engineers, analysts, and business stakeholders.
  • Follow data governance, security, and development best practices within a banking environment.
  • Participate in code reviews, testing, deployment, and production support.
Required Skills
  • 1 3 years of experience in Data Engineering or a related field.
  • Hands-on experience with Snowflake.
  • Strong SQL skills.
  • Experience with DBT (Data Build Tool).
  • Understanding of ETL/ELT concepts and data warehousing.
  • Knowledge of data modeling concepts.
  • Experience with Git/version control.
  • Good analytical and troubleshooting skills.
  • Ability to work onsite in Rhode Island.
Preferred
  • Banking or financial services experience.
  • Experience with cloud-based data platforms.
  • Familiarity with Python or scripting.
  • Exposure to CI/CD and automated data pipeline deployment.
  • Understanding of data quality and governance practices.

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