Develop the data-driven culture within the company;
Develop processes for data processing, storage, cleaning, and enrichment;
Design and maintain data pipelines from collection to consumption;
Create infrastructure for storing and processing large datasets on K8S, Terraform;
Automate testing, validation, and monitoring of data;
Participate in system design and architectural decision-making;
Languages: Python, SQL;
Frameworks: Spark, Apache Beam;
Storage and analytics: BigQuery, GCS, S3, Trino, other GCP and AWS stack components;
Integration: Apache Kafka, Google Pub/Sub, Debezium, Zero ETL;
ETL: Airflow2;
Infrastructure: Kubernetes, Terraform;
Development: GitHub, GitHub Actions, Jira.

Qualifications

Expert in Python 3.7+, experience with PySpark;
Deep knowledge of SQL;
Extensive experience building ETLs with Airflow2;
Industrial experience with Kubernetes;
Understanding of data processing principles and algorithms;
Excellent knowledge of OOP, design patterns, clean architecture;
Proactivity, responsibility, and the ability to take ownership;

Would be a plus:
Experience with high-load services;
DevOps skills and CI/CD automation experience.

Conditions & Benefits

Stable salary, official employment;
Health insurance;
Hybrid work mode and flexile schedule;
Relocation package offered for candidates from other regions;
Access to professional counseling services including psychological, financial, and legal support;
Discount club membership;
Diverse internal training programs;
Partially or fully payed additional training courses;
All necessary work equipment.