Senior Snowflake Developer

DataArt; Georgia; On-site; USD 120,000 - 180,000; Full time

Job summary

DataArt is seeking an experienced Senior Snowflake Data Engineer to lead a high-volume migration from MySQL to Snowflake and to architect reliable, maintainable data workflows. You will design end-to-end Snowflake architecture, build resilient ingestion pipelines, and implement robust testing and version control for SQL code.

You will work with DBT, Airflow, and related tools to optimize performance and cost across Snowflake workloads while collaborating with cross-functional teams on migration,

Qualifications

• 3+ years of hands on Snowflake engineering experience, including tables, stages, file formats, tasks, streams, and Snowflake SQL.
• Hands‑on experience with AWS.
• Strong understanding of ELT and ETL pipeline design in a cloud data warehouse environment.
• Proven experience migrating data workloads from relational databases such as MySQL or PostgreSQL to Snowflake or a similar platform.
• Experience with data transformation frameworks such as DBT, Airflow, Airbyte, or equivalent.
• Proficiency in SQL and at least one scripting language, with Python preferred.
• Experience working with complex, messy, or irregular file formats and building resilient ingestion pipelines.
• Solid understanding of CI and CD for data workflows using GitHub Actions, GitLab CI, or similar tools.
• Familiarity with data modelling best practices such as Kimball, Data Vault, or staging refined gold patterns.

Responsibilities

• Plan and contribute to the migration of data workloads from MySQL to Snowflake.
• Design end to end Snowflake architecture for the target data platform.
• Develop and rebuild ETL and ELT workflows for hundreds of complex sales file formats.
• Build resilient ingestion pipelines for complex, messy, or irregular file formats.
• Contribute to CI and CD, testing, and version controlled SQL practices for data workflows.
• Support performance and cost optimisation across Snowflake workloads.
• Collaborate with cross functional teams on migration, architecture, and delivery activities.

Skills

Snowflake

AWS

SQL

Python

DBT

Airflow

CI/CD

GitHub Actions

Data Modeling

ETL/ELT design

Tools

DBT

Airflow

Airbyte

GitHub Actions

GitLab CI

Job description

We are looking for an experienced Senior Snowflake Data Engineer to support the migration of a high volume database and help shape reliable, maintainable data workflows in Snowflake.

This initiative is centered on a large scale data platform migration from MySQL to Snowflake. The work includes end to end Snowflake architecture, resilient ingestion pipelines, and improved engineering practices such as CI and CD, testing, and version controlled SQL.

• Plan and contribute to the migration of data workloads from MySQL to Snowflake
• Design end to end Snowflake architecture for the target data platform
• Develop and rebuild ETL and ELT workflows for hundreds of complex sales file formats
• Build resilient ingestion pipelines for complex, messy, or irregular file formats
• Contribute to CI and CD, testing, and version controlled SQL practices for data workflows
• Support performance and cost optimisation across Snowflake workloads
• Collaborate with cross functional teams on migration, architecture, and delivery activities

• 3+ years of hands on Snowflake engineering experience, including tables, stages, file formats, tasks, streams, and Snowflake SQL
• Hands‑on experience with AWS
• Strong understanding of ELT and ETL pipeline design in a cloud data warehouse environment
• Proven experience migrating data workloads from relational databases such as MySQL or PostgreSQL to Snowflake or a similar platform
• Experience with data transformation frameworks such as DBT, Airflow, Airbyte, or equivalent
• Proficiency in SQL and at least one scripting language, with Python preferred
• Experience working with complex, messy, or irregular file formats and building resilient ingestion pipelines
• Solid understanding of CI and CD for data workflows using GitHub Actions, GitLab CI, or similar tools
• Familiarity with data modelling best practices such as Kimball, Data Vault, or staging refined gold patterns