Junior Snowflake Engineer

Job Summary

ArisData.ai is seeking a motivated and hands-on Junior Snowflake Engineer to join our data engineering team. The ideal candidate will have practical experience with Snowflake, strong SQL skills, working knowledge of Python, and a good understanding of data engineering and data warehousing concepts.

The candidate will work closely with senior engineers and architects to develop, maintain, test, and troubleshoot scalable data solutions on the Snowflake platform.

Key Responsibilities

Develop and maintain data pipelines and data processing solutions using Snowflake.

Write SQL queries, transformations, stored procedures, and other Snowflake objects.

Assist in developing ETL/ELT pipelines using SQL, Python, and Snowpark.

Work with Snowflake features such as Snowpipe, Streams, Tasks, and Dynamic Tables under the guidance of senior engineers.

Assist in building batch and near-real-time data ingestion pipelines.

Support the development and maintenance of dimensional and analytical data models.

Integrate Snowflake with cloud storage, source systems, ETL/ELT tools, and BI platforms.

Implement data validation, data quality checks, and basic monitoring processes.

Assist with Snowflake security configurations, including RBAC, roles, access controls, and data masking.

Write optimized SQL and assist with Snowflake performance and cost optimization.

Support data warehouse migration and modernization projects.

Use Git and CI/CD processes for version control and automated deployments.

Troubleshoot data pipeline and production issues with support from senior engineers.

Participate in code reviews, testing, documentation, and production deployments.

Collaborate with architects, senior engineers, analysts, and customer teams to understand requirements and deliver solutions.

Core Technical Skills

Snowflake

Hands-on experience with Snowflake.

Understanding of Snowflake architecture and core concepts.

Working knowledge of Snowpark, Snowpipe, Streams & Tasks, and Dynamic Tables.

Basic understanding of RBAC, data masking, secure data access, and Snowflake security.

Understanding of Snowflake performance optimization and cost management.

Programming

Strong SQL skills.

Working knowledge of Python.

Familiarity with Snowpark Python is an advantage.

Data Engineering

Understanding of ETL/ELT concepts.

Basic understanding of data warehousing and dimensional data modeling.

Experience working with batch data pipelines.

Understanding of data quality and validation practices.

Cloud

Exposure to at least one major cloud platform: AWS, Azure, or GCP.

Basic understanding of cloud storage and data integration concepts.

Integration & Data Tools

Exposure to one or more of the following is preferred:

dbt

Fivetran

Matillion

Informatica

Azure Data Factory

AWS Glue

Airbyte

DevOps

Basic experience with Git and version control.

Understanding of CI/CD and automated deployment practices is preferred.

Required Qualifications

1–2 years of experience in data engineering, data warehousing, analytics engineering, or a related field.

At least 1 year of hands-on Snowflake development experience.

Strong SQL development skills.

Working knowledge of Python.

Experience or practical exposure to building ETL/ELT pipelines.

Good understanding of data warehousing and data modeling fundamentals.

Exposure to at least one major cloud platform: AWS, Azure, or GCP.

Understanding of Snowflake performance and security fundamentals.

Strong troubleshooting and problem-solving skills.

Good written and verbal communication skills.

Ability to learn new technologies and work effectively with senior engineers and architects.

Mandatory Certification

Snowflake SnowPro Core Certification is mandatory.

Candidates must hold a valid SnowPro Core certification at the time of application.

Preferred Qualifications

Experience working on production Snowflake projects.

Hands-on experience with Snowpipe, Streams, Tasks, Dynamic Tables, or Snowpark.

Experience with dbt or another modern data transformation/ETL tool.

Experience with cloud data warehouse or ETL migration projects.

AWS, Azure, or GCP certification.

Exposure to CI/CD and automated deployment pipelines.

Internship, academic, or personal project experience involving Snowflake and data engineering is an advantage.

What We're Looking For

We are looking for a Junior Data Engineer with strong Snowflake fundamentals who is eager to build a career in modern data engineering.

Candidates should be able to explain the Snowflake projects they have personally worked on, including:

Data pipelines or ETL/ELT processes they developed or supported.

SQL queries and transformations they created.

Data models they worked with.

Snowflake features they have used.

Data quality or validation processes they implemented.

Performance or troubleshooting issues they encountered and helped resolve.

Their specific contribution to the project.

The ideal candidate should have a strong learning mindset, attention to detail, and the ability to gradually take ownership of Snowflake development tasks while working closely with experienced engineers and architects.

Seniority level: Entry level

Employment type: Full-time

Industries: Data Infrastructure and Analytics