Snowflake/Python Developer

Phyton Talent Advisors; Jersey City (NJ); Presencial; USD 110.000 - 160.000; Jornada completa

Descripción de la vacante

Phyton Talent Advisors in Jersey City, NJ is seeking a data/analytics engineer to design, build, and maintain scalable dbt models and ETL pipelines in Snowflake. You will collaborate with analysts and developers, implement data security, and participate in Agile ceremonies.

The ideal candidate has 3–5+ years in data engineering, strong SQL, dbt, Snowflake, Airflow, and experience with AWS. This onsite role requires on-site interviews next week in Jersey City.

Formación

• 3–5+ years of data engineering or analytics engineering experience.
• Strong SQL and data transformation skills with dbt core/cloud.
• Experience building pipelines in Snowflake and Airflow.
• Familiarity with data modeling (Kimball/Dimensional).

Responsabilidades

• Design, build, and maintain dbt models and pipelines.
• Write Python operators in dbt flow and craft Jinja macros.
• Develop data warehouses using Snowflake.
• Load data from multiple sources via ETL/ELT pipelines.
• Optimize Snowflake performance and manage clustering.
• Implement data security and access controls.
• Collaborate with engineers and analysts to translate requirements into models.
• Ensure data quality through testing and documentation.
• Participate in Agile ceremonies and manage tasks with Jira.
• Integrate dbt into CI/CD pipelines and monitor pipelines.

Conocimientos

SQL

dbt

Snowflake

Airflow

Jira

Git

Agile/Scrum

CI/CD

AWS

Data Modeling

Docker

Educación

Bachelor's degree in CS/Data Eng

Herramientas

Snowflake

Airflow

AWS

Sigma

Qlik

Power BI

Docker

Descripción del empleo

*ONSITE INTERVIEW NEXT WEEK IN JERSEY CITY, NJ. NO EXCEPTIONS FOR VIRTUAL!!**

*DO NOT APPLY IF YOU CANNOT GO ONSITE FOR INTERVIEW*

Key Responsibilities

• Design, build, and maintain scalable, modular dbt models and transformation pipelines using DBT Core.
• Understand DBT Architecture thoroughly and experience in writing Python operators in DBT flow. Strong experience in writing Jinja code, macros, seeds etc.
• Design and develop data warehouses using Snowflake.
• Build and maintain ETL/ELT pipelines to load data from multiple sources.
• Optimize Snowflake performance (Clustering, Warehouses, Query tuning).
• Implement data security (roles, access control, masking)
• Knowledge of data modeling techniques like data vault and dimensional modeling (Kimball/Inmon).
• Automate workflows using data orchestration tools (Apache Airflow or Snowflake Tasks)
• Collaborate with full-stack developers and UI/UX engineers to support application features that rely on transformed datasets.
• Work closely with analysts and stakeholders to gather data requirements and translate them into reliable data models.
• Enforce data quality through rigorous testing, documentation, and version control in dbt.
• Participate in Agile ceremonies (e.g., stand-ups, sprint planning) and manage tasks using Jira.
• Integrate dbt into CI/CD pipelines and support automated deployment practices.
• Monitor data performance and pipeline reliability, and proactively resolve issues.

Mandatory Qualifications & Skills

• 3–5+ years of experience in data engineering or analytics engineering, with a focus on SQL-based data transformation.
• Hands-on production experience using dbt core or dbt cloud as a primary development tool.
• Strong command of SQL and solid understanding of data modeling best practices (e.g., star/snowflake schema).
• Proven experience with Snowflake as a cloud data warehouse.
• Familiarity with Git-based version control workflows.
• Strong communication and collaboration skills, with the ability to work across engineering and business teams.
• Experience working in Agile/Scrum environments and managing work using Jira.
• Nice-to-Have Skills Exposure to CI/CD pipelines and integrating dbt into automated workflows.
• Experience with cloud platforms such as AWS.
• Understanding of how data is consumed in downstream analytics tools (e.g., Sigma, Qlik, Power BI).
• Familiarity with Docker and container-based development.

Education & Experience

• Bachelor’s degree in computer science, Data Engineering, or related field.
• A track record of building and maintaining scalable dbt projects in a production setting with Snowflake and Airflow.
• Experience working in cross-functional teams involving developers, analysts, and product managers.
• A strong sense of ownership, documentation habits, and attention to data quality and performance.