Entry-Level Data Engineer: ETL, SQL & Azure in Austin

Fourhands; Austin (TX); Hybrid; USD 85,000 - 110,000; Full time

Job summary

Four Hands in Austin, TX is seeking an Entry Level Data Engineer to help build and support data pipelines, ETL/ELT processes, and analytics-ready datasets across ERP, eCommerce, and analytics platforms.

You will write SQL, use Python to automate data workflows, and collaborate with data, development, and IT teams while learning Azure data services.

The role offers a hybrid work model in Austin and a path to grow with modern data engineering practices and AI initiatives.

Qualifications

• Bachelor's degree in a related technical field, or equivalent experience.
• Foundational programming with Python strongly preferred.
• Experience with SQL and relational databases.
• Basic understanding of database concepts (tables, joins, keys).
• Exposure to ETL/ELT, data pipelines, data transformation, or data integration.
• Interest in how data moves between systems and supports analytics.

Responsibilities

• Build, maintain, and support data pipelines and ETL/ELT processes across enterprise systems, databases, and cloud environments.
• Write SQL queries to extract, transform, validate, and analyze data.
• Use Python to automate data processing and workflows.
• Help integrate data from ERP, WMS, CRM, eCommerce, and third-party platforms.
• Monitor data pipelines and troubleshoot data quality issues.

Skills

Python

SQL

Git

Cloud Platforms

Data Integration

Education

Bachelor's degree or equivalent experience

Tools

Azure Data Factory

Databricks

Snowflake

dbt

Airflow

Job description

Four Hands in Austin, TX is seeking an Entry Level Data Engineer to help build and support data pipelines, ETL/ELT processes, and analytics-ready datasets across ERP, eCommerce, and analytics platforms.

You will write SQL, use Python to automate data workflows, and collaborate with data, development, and IT teams while learning Azure data services.

The role offers a hybrid work model in Austin and a path to grow with modern data engineering practices and AI initiatives.