Finance Data Engineer - Snowflake & dbt

Phyton Talent Advisors

Jersey City (NJ)

On-site

USD 110,000 - 160,000

Full time

43 hours ago
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Job summary

Phyton Talent Advisors is seeking a Data Engineer to design, build, and maintain dbt-based transformation pipelines in a Snowflake environment. You will collaborate with backend and frontend engineers, product managers, and analysts to create analytics-ready data models that power application features, reporting, and strategic insights.

The role emphasizes clean data design, modern tooling, and hands-on implementation of data warehouses, ETL/ELT pipelines, data quality, and CI/CD integration

Qualifications

  • Bachelor’s degree in computer science or a related field.
  • 3–5 years of data/analytics engineering focusing on SQL-based transformations.
  • Hands-on experience with dbt core/cloud as a primary development tool.
  • Strong SQL and data modeling knowledge (star/snowflake).

Responsibilities

  • Design, build, and maintain scalable dbt models and transformation pipelines.
  • Develop data warehouses using Snowflake and optimize performance.
  • Build and maintain ETL/ELT pipelines from multiple sources.
  • Enforce data quality with tests and version control in dbt.
  • Collaborate with engineers, product managers, and analysts.
  • Participate in Agile ceremonies and manage tasks with Jira.

Skills

SQL
dbt Core/Cloud
Data modeling
Git
Agile/Scrum teamwork
Analytical thinking

Education

Bachelor’s degree in Computer Science / Data Engineering

Tools

dbt Core
Snowflake
Airflow
Jira
Python
Git

Job description

Phyton Talent Advisors is seeking a Data Engineer to design, build, and maintain dbt-based transformation pipelines in a Snowflake environment. You will collaborate with backend and frontend engineers, product managers, and analysts to create analytics-ready data models that power application features, reporting, and strategic insights.

The role emphasizes clean data design, modern tooling, and hands-on implementation of data warehouses, ETL/ELT pipelines, data quality, and CI/CD integration

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