Smart IT Frame LLC
Snowflake Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Snowflake Data Engineer in Portland, Oregon, with a contract length of unspecified duration. The pay rate is also unspecified. Candidates need 6 years of data engineering experience, strong Python skills, and expertise in Snowflake and AWS services.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 25, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Portland, Oregon Metropolitan Area
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🧠 - Skills detailed
#Scala #Automation #API (Application Programming Interface) #Snowflake #Airflow #Lambda (AWS Lambda) #Data Lake #GIT #Data Engineering #Python #AWS (Amazon Web Services) #Data Processing #Version Control #Data Modeling #Redshift #Cloud #Data Pipeline #Databases #S3 (Amazon Simple Storage Service) #"ETL (Extract #Transform #Load)"
Role description
Role - Snowflake Data Engineer
Location - Portland,Oregon Onsite
Job Description
Design, build, and maintain scalable ELT pipelines using Python and Snowflake.
Develop and optimize Snowflake schemas, warehouses, and queries for high performance.
Integrate diverse data sources (APIs, streaming data, relational databases) into AWS-based data lakes.
Implement orchestration workflows using tools like Airflow or AWS Step Functions.
6 years of experience in data engineering or a related field.
Strong proficiency in Python for data processing, automation, and API integration.
Hands-on expertise with Snowflake—data modeling, performance tuning, and query optimization.
Solid experience with AWS services such as S3, Lambda, Glue, Redshift, and CloudWatch.
Familiarity with CI/CD for data pipelines and version control (Git).
Knowledge of data warehousing concepts, dimensional modeling, and ETL/ELT best practices.
Role - Snowflake Data Engineer
Location - Portland,Oregon Onsite
Job Description
Design, build, and maintain scalable ELT pipelines using Python and Snowflake.
Develop and optimize Snowflake schemas, warehouses, and queries for high performance.
Integrate diverse data sources (APIs, streaming data, relational databases) into AWS-based data lakes.
Implement orchestration workflows using tools like Airflow or AWS Step Functions.
6 years of experience in data engineering or a related field.
Strong proficiency in Python for data processing, automation, and API integration.
Hands-on expertise with Snowflake—data modeling, performance tuning, and query optimization.
Solid experience with AWS services such as S3, Lambda, Glue, Redshift, and CloudWatch.
Familiarity with CI/CD for data pipelines and version control (Git).
Knowledge of data warehousing concepts, dimensional modeling, and ETL/ELT best practices.
