TL;DR

Senior Data Engineer (Python/SQL): Designing, implementing, and optimizing data pipelines and ETL processes with an accent on performance, scalability, and reliability. Focus on developing efficient workflows and collaborating with cross-functional teams.

Location: Fully remote

Company

%hirify_global% is an American global software development company headquartered in Miami, FL, with an office in Chicago, IL.

What you will do

Develop and optimize ETL workflows using Python and SQL.
Design and implement scalable data pipelines for processing various data sources.
Work with relational databases (e.g., PostgreSQL, Oracle) to ensure efficient data storage and retrieval.
Optimize SQL queries and Python scripts for performance and maintainability.
Implement robust error handling, logging, and monitoring for data processing pipelines.
Collaborate with cross-functional teams to integrate and manage data sources.

Requirements

5+ years of experience in Data Engineering.
Expert-level Python and SQL skills – ability to write efficient, scalable, and maintainable code.
Strong experience in designing ETL processes and working with large datasets.
Solid understanding of database performance tuning and query optimization.
Experience with data modeling and schema design.
Familiarity with cloud storage solutions (Azure, AWS, or GCP).
Strong problem-solving skills and ability to work independently.

Nice to have

Experience with PySpark, orchestrators and knowledge of CI/CD for deployment process automation.

Benefits

Flexible working conditions and a cooperative environment.
Competitive salary.
Growth opportunities, skills and competencies improvement, and professional certification.
In-company training (English, Software / DevOps / Project management / Design / Business).