Data Engineer (Python/PySpark)

TL;DR

Data Engineer (Python/PySpark): Building a large-scale data infrastructure for analytics, machine learning, and real-time recommendations with an accent on ETL processes, big data storage, and high-load API optimization. Focus on designing scalable data pipelines using PySpark and Airflow and managing infrastructure via Kubernetes and Terraform.

Location: Hybrid (Almaty, Kazakhstan)

Company

hirify.global is a global tech company providing ride-hailing, freight, and delivery services focused on fair pricing and people-first solutions.

What you will do

• Create and maintain a unified system for processing, storing, and validating data to ensure integrity and accessibility.
• Design and build end-to-end data pipelines from capture to consumer presentation.
• Develop infrastructure for big data storage and processing using Kubernetes (K8s) and Terraform.
• Optimize REST and gRPC APIs for high-load data access services.
• Write integration/unit tests and develop automation tools for data validation and alerting.
• Contribute to high-level system design and architecture.

Requirements

• Advanced proficiency in Python 3.7+ and strong experience in developing ETL processes using PySpark.
• Proven experience developing data flows with Airflow2.
• High level of expertise in SQL, including complex queries and optimization.
• Industrial experience with Kubernetes (K8s).
• Strong understanding of Spark/Flink and data processing algorithms.
• Solid knowledge of OOP, design patterns, and pure architecture.

Culture & Benefits

• Access to mentoring, career consulting, and professional learning programs.
• Global Talent Exchange Program for gaining international experience.
• Co-financed language courses and internal speaking clubs.
• Engagement in company-wide challenges, sports activities, and social impact projects.
• Collaborative environment with a focus on initiative and open communication.

Hiring process

• Application review.
• Job offer.
• Hiring.