Data Engineer, Public Health & Cloud Pipelines

Guidehouse; Houston (TX); On-site; USD 65,000 - 90,000; Full time

Benefits offered by this job

Medical Insurance

401(k) Plan

Tuition Reimbursement

Paid Holidays

Job summary

Guidehouse is seeking an early-career Data Engineer to develop and maintain data pipelines, ETL/ELT processes, and cloud-based analytics solutions. The role emphasizes learning and collaboration in a data-driven environment, with opportunities to work on AWS and Azure integrations and modern data platforms.

You will contribute to data modeling, scripting in Python/SQL, and supporting CI/CD practices while growing your skills across data engineering and analytics domains.

Qualifications

• Bachelor's degree in a technical field or related experience.
• 2+ years of experience in data engineering, software engineering, or related discipline.
• Experience with Python, SQL, and cloud platforms (AWS/Azure).
• Familiarity with ETL/ELT, data warehousing, and data integration concepts.

Responsibilities

• Develop, test, and maintain data pipelines and ETL/ELT processes.
• Support cloud-based data environments in AWS and Azure.
• Contribute to data modeling, databases, and data solutions.
• Write scripts and applications in Python/SQL/PySpark.
• Collaborate with engineers, analysts, and stakeholders to deliver solutions.
• Support CI/CD practices and version control with Git.

Skills

Python

SQL

PySpark

Git

Cloud (AWS)

Azure

ETL/ELT

Data Pipelines

Data Modeling

QA/Data Validation

Education

Bachelor's degree in CS/DS/IS/Engineering/Math

Tools

AWS

Azure Data Factory

Databricks/Spark

Power BI/Tableau

Job description

Guidehouse is seeking an early-career Data Engineer to develop and maintain data pipelines, ETL/ELT processes, and cloud-based analytics solutions. The role emphasizes learning and collaboration in a data-driven environment, with opportunities to work on AWS and Azure integrations and modern data platforms.

You will contribute to data modeling, scripting in Python/SQL, and supporting CI/CD practices while growing your skills across data engineering and analytics domains.