Snowflake Data Architect — AWS, DBT & PySpark

Cognizant; Salem (OR); On-site; USD 116,000 - 136,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays + Paid Time Off

401(k) plan and contributions

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant is seeking a skilled Data Engineer to support Life Sciences data engineering initiatives. The role focuses on building scalable data pipelines, ETL/ELT processes, and end-to-end data workflows in cloud environments using Snowflake, AWS, DBT, Python, PySpark, and Unix.

The candidate will design data transformation models, ensure data quality and governance, and collaborate with stakeholders to meet business objectives while supporting data integration and modernization efforts in Life

Qualifications

• Hands-on experience with Snowflake Data Warehouse.
• Expertise in AWS Cloud Services and cloud-based data architecture.
• Experience with DBT for data transformation and modeling.
• Proficiency in Python and PySpark for data processing and automation.
• Strong understanding of ETL/ELT frameworks, data integration, and pipeline orchestration.
• Experience with Unix/Linux scripting and environment management.
• Knowledge of SQL optimization, data modeling, and database design principles.
• Familiarity with CI/CD practices and version control tools such as Git.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Snowflake, AWS, Python, and PySpark.

Skills

Snowflake

AWS

DBT

Python

PySpark

Unix/Linux

SQL optimization

Data integration

CI/CD

Git

Job description

Cognizant is seeking a skilled Data Engineer to support Life Sciences data engineering initiatives. The role focuses on building scalable data pipelines, ETL/ELT processes, and end-to-end data workflows in cloud environments using Snowflake, AWS, DBT, Python, PySpark, and Unix.

The candidate will design data transformation models, ensure data quality and governance, and collaborate with stakeholders to meet business objectives while supporting data integration and modernization efforts in Life