Data Engineer

We are looking for an experienced and highly skilled Data Engineer with strong background in building and managing robust data pipelines, working with large-scale datasets, and ensuring data availability for analytical and operational purposes.

Responsibilities:

• design, develop, and maintain scalable and reliable data pipelines to handle large volumes of structured and unstructured data;

• work with cross-functional teams to understand data needs and deliver efficient data solutions;

• implement and optimize ETL (Extract, Transform, Load) processes for data integration from various sources;

• build and maintain data architectures, ensuring that data is accessible, accurate, and up-to-date for the business and analytics teams;

• develop data models and support data warehousing solutions to ensure efficient data storage and retrieval;

• collaborate with Data Scientists, Analysts, and other teams to facilitate data analysis and decision-making processes;

• continuously monitor, test, and improve data systems to ensure they meet business requirements and perform at scale;

• ensure data quality and security, implementing best practices for data governance.

• document data systems and workflows for transparency and operational continuity.

Requirements:

• 5+ years of professional experience in Data Engineering or similar roles;

• strong proficiency in SQL, Python, and other data engineering tools;

• experience with cloud platforms (Azure, AWS, GCP) and relevant tools for data processing and storage;

• extensive experience with building and maintaining ETL pipelines using tools like Apache Airflow, Talend, or similar;

• strong understanding of data modeling, data warehousing, and big data technologies (e.g., Hadoop, Spark, Databricks);

• experience with data lake architectures and storage solutions;

• familiarity with containerization tools (e.g., Docker, Kubernetes);

• experience working in agile environments with CI/CD processes;

• ability to troubleshoot and optimize data systems for maximum performance;

• strong problem-solving skills and attention to detail;

• English proficiency at B2 level or higher.

• Tech Stack:

1. Languages: Python (pandas, numpy, pySpark), SQL

2. Platforms: Azure, AWS, GCP, Databricks, Hadoop

3. Tools: Apache Airflow, Talend, Spark, Kafka, Docker, Kubernetes

4. Methods: ETL, Data Warehousing, Data Lake architecture

5. Processes: CI/CD, Agile/Scrum

• Nice to also have:

1. Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).

2. Experience with Machine Learning infrastructure or MLOps pipelines.

3. Background in distributed systems or microservices architecture.

Conditions:

• Official employment under the Labor Code of Kazakhstan

• Remote format with an option to work from the office

• International projects and team