AI-Powered Data Engineer: Pipelines & Cloud

Guidehouse; Chicago (IL); On-site; USD 89,000 - 148,000; Full time

Benefits offered by this job

Medical insurance

Dental & Vision insurance

401(k) retirement plan

Parental leave

Professional development

Job summary

Guidehouse is seeking a Data Engineer with AI exposure to design, build, and optimize data pipelines and analytics platforms. You will work with SQL, Python, Java, PySpark, and REST/SOAP APIs, and help implement CI/CD for data workflows.

The role involves Azure Functions, Docker/Kubernetes, and collaboration with DBAs and developers to ensure data quality and reliability. The ideal candidate has 5+ years in data engineering, experience with Databricks, Git-based workflows, and Agile development

Qualifications

• Bachelor’s degree required.
• 5+ years of data engineering or related experience.
• Experience with Java, Python, SQL, PySpark and API development.

Responsibilities

• Design, develop, test and maintain data pipelines and ETL processes.
• Build and optimize data architectures and models for analytics.
• Implement and manage CI/CD pipelines for data workflows.
• Develop and deploy cloud-based solutions using Azure Functions and containers.
• Collaborate with DBAs and application developers to integrate data models and APIs.
• Ensure data quality, validation, monitoring, and logging.

Skills

Java

Python

SQL

PySpark

APIs (REST/SOAP)

Git

CI/CD

Databricks

Kubernetes

Agile development

Education

Bachelor's degree

Tools

Databricks

Git

Jira

Confluence

Kubernetes

Docker

Azure Functions

Job description

Guidehouse is seeking a Data Engineer with AI exposure to design, build, and optimize data pipelines and analytics platforms. You will work with SQL, Python, Java, PySpark, and REST/SOAP APIs, and help implement CI/CD for data workflows.

The role involves Azure Functions, Docker/Kubernetes, and collaboration with DBAs and developers to ensure data quality and reliability. The ideal candidate has 5+ years in data engineering, experience with Databricks, Git-based workflows, and Agile development