Cloud Data Engineer II: AWS Pipelines & Dashboards

Aaisonline; United States; Remote; USD 72,000 - 88,000; Full time

Job summary

AAIS is seeking a Cloud Data Engineer II to design, build, and support a cloud-based data platform. You will own complete features and work packages, delivering dashboards, visualizations, reports, and datasets for business and tech stakeholders.

The role requires hands-on data engineering in a cloud-native environment with Python as a primary language, experience in AWS, MongoDB Atlas, and Databricks, and strong collaboration across teams.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Management, Cybersecurity, or related discipline, or equivalent practical experience.
• 3+ years of engineering experience delivering production technology solutions.
• Experience delivering complete features or work packages independently.
• Experience in insurance or regulated industries is a plus.
• Must complete an in-person leadership interview and travel up to 5% annually.

Responsibilities

• Independently deliver data features, pipelines, dashboards, reports, and datasets from design through production support.
• Translate requirements into designs, tests, and documentation; manage dependencies and progress.
• Collaborate with engineers, partners, vendors, and platform owners to deliver data solutions.
• Participate in design reviews, code reviews, and agile planning; maintain code in GitHub and work in Azure DevOps.
• Develop dashboards and visualizations to support stakeholders; contribute to best practices and improvements.

Skills

Python

Power BI

Cloud-native

Data engineering

Communication

Education

Bachelor's degree in CS or related field

Tools

AWS

MongoDB Atlas

Databricks

GitHub

Azure DevOps

Job description

AAIS is seeking a Cloud Data Engineer II to design, build, and support a cloud-based data platform. You will own complete features and work packages, delivering dashboards, visualizations, reports, and datasets for business and tech stakeholders.

The role requires hands-on data engineering in a cloud-native environment with Python as a primary language, experience in AWS, MongoDB Atlas, and Databricks, and strong collaboration across teams.