Senior Data Engineer / Analytics Engineer

Rootshell Enterprise Technologies Inc.; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Rootshell Enterprise Technologies Inc. is seeking a Senior Data Engineer / Analytics Engineer to design and optimize modern data pipelines using Snowflake, dbt and AWS in a remote setting.

You will build robust data models, ensure data quality, and collaborate with cross-functional teams to deliver scalable analytics solutions. Git version control and AI-assisted tooling will support development.

Qualifications

• 5+ years data engineering or analytics experience.
• Proficient in Snowflake, dbt, AWS.
• Experience designing scalable data pipelines.
• Strong data modeling and analytics skills.

Responsibilities

• Design and maintain scalable data pipelines.
• Build data models and analytics solutions.
• Optimize ETL/ELT workflows for reliability.
• Collaborate with cross-functional teams to deliver data products.

Skills

Data modeling

ETL/ELT

Analytics engineering

Cloud data pipelines

Collaboration

Tools

Snowflake

dbt

AWS

Git

Job description

Hello All,

Greetings from Rootshell Inc.

Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US. We are actively seeking Senior Data Engineer / Analytics Engineer for one of our client,

Job Title

Senior Data Engineer / Analytics Engineer

Location

Remote

• We are seeking a skilled Senior Data Engineer / Analytics Engineer with strong experience in Snowflake, dbt, AWS, and modern data engineering practices.
• Design, develop, and maintain scalable data pipelines and robust ETL/ELT workflows.
• Build and optimize data models, transformations, and analytics solutions using Snowflake and dbt.
• Leverage AWS services to support cloud-based data processing, storage, and integration.
• Use Git for version control, code management, and collaborative development workflows.
• Ensure data quality, reliability, performance, and consistency across data pipelines and analytics platforms.
• Utilize AI-assisted development tools to improve coding productivity, testing, debugging, and documentation.
• Collaborate with cross-functional teams to deliver reliable, scalable, and business-driven data solutions.