Senior Snowflake Engineer

Tech Stack:

• Snowflake

• AWS

• SQL

• Python

• ETL Development

• Data Warehousing

• Data Modeling

• CI/CD

• Spark (nice to have)

• Azure (Databricks, Synapse, Fabric)

Project Description:

We are looking for a Senior Snowflake Engineer to join a data-focused team responsible for developing, maintaining, and optimizing cloud-based data solutions built on Snowflake within an AWS environment.

In this role, you will work on enhancing existing data platforms, improving data quality, ensuring platform stability, and supporting critical business processes through reliable and scalable data solutions. You will play a key role in troubleshooting production issues, optimizing system performance, and driving cost-efficient data operations.

Required Qualifications:

• 5+ years of experience in Data Engineering

• Strong hands-on experience with Snowflake in AWS environments

• Advanced SQL skills

• Solid programming experience in Python

• Proven experience developing, maintaining, and optimizing data pipelines

• Strong troubleshooting and problem-solving skills

• Experience with performance tuning and cost optimization

• Knowledge of data warehousing concepts and data modeling

• Ability to work effectively in production support and enhancement activities

Nice to Have:

• Experience with Azure services such as Databricks, Synapse, or Fabric

• Familiarity with Apache Spark

• Experience with CI/CD practices and tools

• Knowledge of data governance and data quality frameworks

• Experienced in using AI tools in day-to-day workflow

Scope of Services:

• Develop, maintain, and enhance ETL processes within the Snowflake platform

• Extend and adjust existing data models and warehouse structures

• Monitor, analyze, and improve data quality across the platform

• Administer Snowflake environments, including roles, warehouses, and access management

• Investigate, troubleshoot, and resolve issues within data pipelines and warehouse solutions

• Optimize Snowflake workloads for performance, scalability, and cost efficiency

• Collaborate with data engineering teams and stakeholders to deliver reliable data solutions

• Support operational excellence and continuous improvement initiatives within the data platform ecosystem

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