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Salary
≈ $14k – $39k per year (Estimated)
Location
In office (Almaty)
Seniority
Middle · 2+ years exp

First seen by Alion on Aug 26, 2026. Bank CenterCredit scores C on the Alion truth index.

Overview
Company
Impact
Profile match
Bank CenterCredit is one of the oldest, largest, and most technologically advanced commercial banks in Kazakhstan, headquartered in Almaty. Founded in 1988, the financial institution operates on a universal banking model, providing comprehensive retail banking, SME financing, corporate lending, digital wealth management, and treasury services across a nationwide branch network and digital ecosystem.

Основные задачи:

Разработка и сопровождение ETL/ELT-процессов

Нормализация, дедупликация, унификация и консолидация данных из разных источников. Разработка схем данных и построение связей между сущностями.

Работа с Greenplum, PostgreSQL, Oracle Оптимизация SQL-запросов и создание представлений (views, materialized views).

Настройка оркестрации и автоматизации пайплайнов (Airflow и др.).

Контроль качества данных (Data Quality) Поддержка интеграций с аналитическими, ML- и LLM-сервисами.

Опыт работы с микросервисной архитектурой и шлюзами данных API Gateway.

Технические требования Основной стек: Python: опыт написания production-скриптов SQL уверенные знания PostgreSQL, Greenplum, Oracle ETL-инструменты: Airflow Базы данных: опыт проектирования и администрирования реляционных БД.

Работа с API: REST, JSON, XML.

Инфраструктура опыт работы в *Linux / nix-среде, знание Docker, Git. Мониторинг и логи: Grafana.

Будет плюсом: Опыт построения хранилищ данных (Data Lake, Data Warehouse).

Опыт интеграции с ML/LLM-сервисами или аналитическими платформами.

Знание архитектуры DWH (ODS, DDS, Staging).

Опыт работы с Kafka, Redis, MinIO, ClickHouse.

Опыт и квалификация От 2 до 4 лет опыта работы на позиции Data Engineer / ETL Developer / Python Developer.

  • Практический опыт создания или оптимизации ETL-пайплайнов.

Участие в проектах по интеграции данных из нескольких источников.

  • Понимание принципов качества, надёжности и воспроизводимости данных (DQ, lineage, validation)
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