Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4345191310&distance=25.0&f_AL=true&f_TPR=r86400&f_WT=2&geoId=103644278&keywords=software%20engineer&origin=JOB_SEARCH_PAGE_JOB_FILTER&start=300

Job Description: Snowflake Data Engineer
CloudHive · United States (Remote)

Easy Apply

Save
Save Snowflake Data Engineer  at CloudHive
Show more options
Your profile is missing required qualifications


Show match details

Help me update my profile


BETA

Is this information helpful?



Get personalized tips to stand out to hirers
Find jobs where you’re a top applicant and tailor your resume with the help of AI.

Try Premium for PKR0
Meet the hiring team

Levi L.  
 3rd
President | Snowflake Squad Member | Sales & Technical Sales Pro ❄
Job poster

Message
About the job
CloudHive is your North America and LATAM Snowflake-focused staffing partner. We help accelerate Snowflake adoption and maximize the value of the Snowflake AI Data Cloud by delivering experienced, on-demand Snowflake contractors and specialized talent acquisition services.


You'll lead end-to-end data engineering to design, build, and optimize a multi-layer (Bronze/Silver/Gold) data warehouse for analytics and reporting. This role involves gathering requirements, creating production-ready schemas and pipelines, and delivering validated, secure, analytics-ready data—empowering the client with robust Snowflake solutions. 



Key Responsibilities:



Gather business requirements and design data models for a multi-layer Snowflake data warehouse.
Build ingestion and ELT pipelines using Snowflake features (e.g., warehouses, Streams & Tasks, stages) and SQL for transformations and data quality checks.
Implement data quality validations, performance tuning, and security measures to ensure reliable, analytics-ready data.
Integrate with tools like DevOps Repos for Git-based version control and Power BI for reporting.
Support production deployments, troubleshoot issues, and provide documentation for seamless handover.
Collaborate with stakeholders to optimize pipelines and align with analytics goals.


Requirements:



4+ years of hands-on experience in Snowflake data engineering, including multi-layer warehouse design and ELT processes.
Proficiency in Snowflake (warehouses, Streams & Tasks, stages), advanced SQL, Git-based version control (e.g., DevOps Repos), and Power BI integration.
Strong skills in data modeling, ingestion, transformations, performance optimization, and data quality implementation.
Experience with production deployments and secure, validated data pipelines.