Cloud Data Engineer — ETL Pipelines & Analytics

Jobtailor; Alabama; On-site; USD 95,000 - 130,000; Full time

Job summary

Jobtailor is seeking a data engineer to assist in building and maintaining data pipelines and ETL/ELT processes. You will work with senior engineers to ingest, transform, and load data from various sources, enabling modern data models and cloud-based solutions in AWS and Azure.

You will develop Python, SQL, and PySpark scripts, contribute to CI/CD practices, and help validate data quality across environments.

Qualifications

• Bachelor's degree in a technical field and relevant data engineering experience.
• Foundational knowledge of Python, Java, or SQL and data querying concepts.
• Experience with AWS or Azure and cloud-based data solutions is preferred.
• Exposure to ETL/ELT, data warehousing, and analytics concepts is desirable.
• Internships or projects in data engineering or cloud computing are a plus.

Responsibilities

• Assist in developing, testing, and maintaining data pipelines and ETL/ELT processes.
• Support data models, databases, and cloud-based data solutions.
• Participate in data integration, migration, and modernization initiatives.
• Develop scripts, queries, and applications using Python, SQL, and PySpark.
• Support AWS and Azure cloud environments and CI/CD processes.
• Monitor pipelines, troubleshoot issues, and ensure data quality.

Skills

Python programming

SQL

PySpark

Data integration

ETL

Data warehousing

Data validation

Data modeling

Relational databases

Data querying

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

Azure

Git

Databricks

Power BI

Tableau

Kibana

Job description

Jobtailor is seeking a data engineer to assist in building and maintaining data pipelines and ETL/ELT processes. You will work with senior engineers to ingest, transform, and load data from various sources, enabling modern data models and cloud-based solutions in AWS and Azure.

You will develop Python, SQL, and PySpark scripts, contribute to CI/CD practices, and help validate data quality across environments.