Data Engineer

VRN Technologies; Phoenix (AZ); On-site; USD 120,000 - 160,000; Full time

Job summary

VRN Technologies is seeking an accomplished Data Engineer in Phoenix to design and optimize data pipelines leveraging Snowflake and dbt. You will transform, model, test, and document data assets while implementing robust SQL queries and automated workflows.

The ideal candidate brings 8+ years in data engineering, strong Python scripting skills, and deep experience with cloud platforms. Knowledge of data quality practices and CI/CD pipelines will be highly valued in this role.

Qualifications

• 8+ years of experience in Data Engineering and data pipeline development.
• Strong hands-on experience with Snowflake for cloud data warehousing.
• Strong experience with dbt for data transformation, modeling, testing, and documentation.
• Proficiency in SQL and experience developing complex queries and data transformations.
• Experience building and maintaining ETL/ELT pipelines.
• Strong understanding of dimensional data modeling, star/snowflake schemas, facts, and dimensions.
• Experience with Python for data processing and automation.
• Experience with Git-based version control and CI/CD practices.
• Knowledge of data quality, data validation, testing, and performance optimization.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with orchestration tools such as Airflow, Dagster, or similar is preferred.

Skills

Data Engineering

Data Pipeline Development

SQL

Python

CI/CD practices

Data Quality & Testing

Dimensional Data Modeling

Tools

Snowflake

dbt

Git

Airflow

Dagster

Cloud Platforms (AWS/Azure/GCP)

Job description

• 8+ years of experience in Data Engineering and data pipeline development.
• Strong hands-on experience with Snowflake for cloud data warehousing.
• Strong experience with dbt (Data Build Tool) for data transformation, modeling, testing, and documentation.
• Proficiency in SQL and experience developing complex queries and data transformations.
• Experience building and maintaining ETL/ELT pipelines.
• Strong understanding of dimensional data modeling, star/snowflake schemas, facts, and dimensions.
• Experience with Python for data processing and automation.
• Experience with Git-based version control and CI/CD practices.
• Knowledge of data quality, data validation, testing, and performance optimization.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with orchestration tools such as Airflow, Dagster, or similar is preferred.