Data Engineer — AWS Pipelines & dbt Expert

Smarty, LLC.; Orem (UT); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Life insurance

Paid time off

401(k) with match

Training & development

Job summary

Smarty, LLC. in Orem, UT is hiring a Data Engineer for its Business Intelligence team. You will design, build, and maintain scalable data pipelines and the AWS data lakehouse to power analytics and reporting for stakeholders.

The role emphasizes reliable, well-structured data and close collaboration with data analysts. You’ll implement dbt models and Python pipelines, manage AWS services, orchestrate workflows, and contribute to data quality through testing, documentation, and runbooks in a SaaS

Qualifications

• 3+ years of experience in a Data Engineering or similar role.
• dbt modeling, testing, and documentation.
• Python for data pipeline development.
• AWS data services including S3, Athena, Glue, and Lambda.
• Airbyte deployment and maintenance.
• SQL and data modeling concepts.
• Git/version control and code review workflow.
• Experience with SaaS APIs such as Salesforce, HubSpot, Google Analytics.

Responsibilities

• Design, build, and maintain scalable data pipelines and ELT workflows.
• Develop and maintain dbt models, tests, and docs.
• Manage AWS data lakehouse (S3, Glue, Athena) and orchestration with Step Functions.
• Deploy Lambda functions for near-real-time pipelines and reverse ETL.
• Manage infrastructure as code with CloudFormation.
• Collaborate with data analysts for Power BI reporting and semantic models.
• Monitor pipeline health with CloudWatch and ensure data quality via dbt tests.
• Document data architecture and runbooks.

Skills

dbt

Python

AWS services

SQL

Airbyte

Git

Data modeling

MySQL

ETL pipelines

Power BI

APIs integration

Reverse ETL

Job description

Smarty, LLC. in Orem, UT is hiring a Data Engineer for its Business Intelligence team. You will design, build, and maintain scalable data pipelines and the AWS data lakehouse to power analytics and reporting for stakeholders.

The role emphasizes reliable, well-structured data and close collaboration with data analysts. You’ll implement dbt models and Python pipelines, manage AWS services, orchestrate workflows, and contribute to data quality through testing, documentation, and runbooks in a SaaS