Snowflake Data Engineer [Remote]

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Snowflake Data Engineer based in the United States.

As a Snowflake Data Engineer, you will design, develop, and optimize cloud-based data solutions that transform raw information into reliable, actionable insights. You will build and maintain data pipelines, integrate information from multiple enterprise sources, and develop efficient data models to support analytics and business intelligence initiatives. Working in a remote, project-driven environment, you will collaborate with technical teams to ensure data quality, scalability, and performance across cloud data platforms. You will leverage SQL and modern ETL/ELT practices to streamline data processing and improve warehouse efficiency. This opportunity is ideal for a technically minded professional who enjoys solving complex data challenges and building maintainable, high-performing data infrastructure. The role offers the flexibility of remote work in the United States under a contract-based employment arrangement.

Accountabilities

• Cloud Data Warehouse Development: Develop, maintain, and optimize data warehouse solutions using Snowflake to support business reporting, analytics, and data-driven decision-making.
• Data Pipeline Engineering: Design, build, and maintain ETL/ELT pipelines that extract, transform, and load data efficiently from multiple enterprise source systems into Snowflake.
• SQL Development & Optimization: Write, test, and optimize complex SQL queries and data transformations to improve processing efficiency, query performance, and overall warehouse utilization.
• Data Integration: Integrate data from diverse sources, ensuring consistent, reliable, and accessible information across the organization's data ecosystem.
• Data Modeling & Transformation: Develop and maintain data models, structured datasets, and analytical data layers that meet reporting and business intelligence requirements.
• Python-Based Development: Where applicable, use Python, Snowflake stored procedures, and user-defined functions to automate workflows and implement advanced data processing logic.
• Performance Monitoring & Troubleshooting: Identify and resolve data quality issues, pipeline failures, query bottlenecks, and warehouse performance challenges.
• Cloud Platform & Tool Integration: Work with cloud infrastructure, orchestration tools, and data transformation technologies to support reliable and scalable data workflows.
• Security & Access Management: Support Snowflake security configurations, role-based access controls, and warehouse settings to maintain appropriate data access and platform performance.
• Continuous Improvement: Apply engineering best practices to improve pipeline reliability, maintainability, scalability, and the overall efficiency of data operations.

Requirements

• Snowflake Experience: Hands-on experience developing, implementing, or supporting data solutions on Snowflake, including cloud data warehouse environments.
• SQL Proficiency: Strong SQL skills, with demonstrated ability to develop complex queries, implement data transformations, troubleshoot issues, and optimize query performance.
• ETL/ELT Pipeline Development: Practical experience designing, developing, maintaining, or supporting ETL/ELT pipelines for reliable data ingestion and transformation.
• Data Integration Skills: Experience connecting and consolidating information from multiple source systems into centralized data platforms.
• Data Warehousing & Modeling: Understanding of data warehouse architecture, data modeling principles, and the development of datasets for analytics and reporting.
• Troubleshooting & Performance Optimization: Ability to investigate data discrepancies, diagnose pipeline failures, and improve the performance and reliability of data workflows.
• Python & Advanced Snowflake Capabilities: Familiarity with Python, Snowflake stored procedures, or user-defined functions is preferred.
• Data Integration Tools: Experience with Matillion or other data integration and orchestration platforms is an advantage.
• Cloud & Transformation Technologies: Familiarity with AWS, dbt, or IBM DataStage is desirable.
• Snowflake Administration & Security: Knowledge of role-based access controls, security configurations, and virtual warehouse management is beneficial.
• Analytical & Problem-Solving Skills: Strong attention to detail, logical thinking, and the ability to resolve technical challenges in complex data environments.
• Collaboration & Communication: Ability to work effectively with technical stakeholders, communicate technical issues clearly, and contribute to collaborative project delivery.
• Work Arrangement: Must be able to work remotely from the United States under a contract-based arrangement. Candidates should be prepared to provide their current location and work authorization details during the application process.

Benefits

• Competitive Contract Rate: Indicative hourly compensation of $46–$56 per hour , depending on experience, technical skills, and project requirements.
• Remote Work Flexibility: Work remotely from within the United States.
• Contract-Based Opportunity: Gain experience delivering cloud data engineering solutions in a project-oriented environment.
• In-Demand Technical Skills: Apply and strengthen expertise in Snowflake, SQL, ETL/ELT, data modeling, and cloud data platforms.
• Exposure to Modern Data Technologies: Opportunities to work with complementary technologies such as Python, AWS, dbt, Matillion, and other integration tools, depending on project needs.
• Technical Growth: Develop practical experience in data pipeline optimization, cloud warehouse performance, data integration, and scalable data architecture.
• Collaborative Environment: Work alongside technical professionals to solve data challenges and deliver reliable, maintainable data solutions.
• Employment Type: Contract.
• Experience Level: Entry-level listing, with hands-on Snowflake and data engineering experience required.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.