Senior Remote Data Engineer — Airflow & ETL Specialist

Intetics; Poland; On-site; PLN 180,000 - 260,000; Full time

Job summary

Intetics Inc. is seeking a Senior Data Engineer / Apache Airflow Specialist to join our distributed team. You will design, implement, and optimize large-scale ETL pipelines using Airflow, manage Oracle and PostgreSQL performance, and support Elasticsearch integration for fast data retrieval.

You will ensure smooth deployment pipelines in GitLab and collaborate with engineers to enhance data quality and reliability across complex processes.

Qualifications

• 3+ years of Apache Airflow DAG orchestration.
• 5+ years of Python (ETL focus) with Flask API experience as a plus.
• 3+ years of Elasticsearch (data indexing & optimization).
• 3+ years of Unix/Linux scripting & operations.
• 3+ years with Oracle or PostgreSQL (ideally both).
• 3+ years of GitLab pipelines (build/test/deploy).
• Advanced English and a technical degree.

Responsibilities

• Develop, orchestrate, and maintain complex Apache Airflow DAGs for ETL/workflow pipelines.
• Build and optimize Python-based ETL scripts, integrating with Flask APIs as needed.
• Design and manage Elasticsearch indexing and performance tuning workflows.
• Handle Unix/Linux scripting and operations for automation and monitoring.
• Work with Oracle and PostgreSQL databases for large-scale data processing.
• Implement and maintain GitLab CI/CD pipelines for build, test, and deploy.
• Collaborate with the team to ensure scalability, reliability, and quality of data solutions.

Skills

Apache Airflow

Python

Elasticsearch

Unix/Linux scripting

Oracle

PostgreSQL

GitLab

Education

Technical degree

Tools

Flask

Job description

Intetics Inc. is seeking a Senior Data Engineer / Apache Airflow Specialist to join our distributed team. You will design, implement, and optimize large-scale ETL pipelines using Airflow, manage Oracle and PostgreSQL performance, and support Elasticsearch integration for fast data retrieval.

You will ensure smooth deployment pipelines in GitLab and collaborate with engineers to enhance data quality and reliability across complex processes.