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Data Engineer (Data Delivery)

Hybrid - Middle

Kazakhstan, Almaty

We are looking for Data Engineer to join the Data Integration team.

You will be working with cutting edge technologies (GCP, AWS, BigQuery, Kafka, K8s) and building a large scale data infrastructure for analytics, machine learning, and realtime recommendations.

Apply for this position

Responsibilities

  • 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
  • Develop APIs (REST, gRPC) for highload services
  • 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

Qualifications

  • Expert in Python 3.7+,
  • Experience with PySpark Deep knowledge of SQL
  • Extensive experience building ETLs with Air flow 2
  • Industrial experience with Kubernetes
  • Understanding of data processing principles and algorithms
  • Excellent knowledge of OOP, design patterns, clean architecture
  • Productivity, responsibility, and the ability to take ownership
  • Would be a plus: Experience with highload services DevOps skills and CI/CD automation experience If you’re interested in working with big data, complex challenges, and cutting edge technologies, we’d love to meet you!

Conditions & Benefits

  • Stable salary, official employment
  • Health insurance
  • Hybrid work mode and flexible schedule
  • Relocation package offered for candidates from other regions (only for Kazakhstan and Cyprus)
  • Access to professional counseling services including psychological, financial, and legal support
  • Discount club membership
  • Diverse internal training programs
  • Partially or fully paid additional training courses
  • All necessary work equipment

Our tech stack:

  • Languages: Python, SQL
  • Frameworks: Spark, Apache Flink
  • Storage and analytics: BigQuery, GCS, S3, Trino, other GCP and AWS tools
  • Components Integration: Apache Kafka, Google Pub/Sub, Debezium
  • ETL Orchestration: Airflow 2
  • Infrastructure: Kubernetes, Terraform
  • Development: GitHub, GitHub Actions, Jira

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