Key skills
AirflowDockerETLJavaScriptKafkaMongoDBNode.jsPythonTypeScriptELTData LakeAnalyticsS3Git
About this role
Role Overview
- Design and evolve the architecture of the data platform and storage systems.
- Build reliable ETL/ELT processes and develop scalable data pipelines for delivering data into a centralized analytical warehouse.
- Maintain and further develop the Data Warehouse.
- Collaborate with engineering and analytics teams on system design and architectural decisions.
- Ensure data governance and maintain high standards of data quality.
- Write and optimize queries for MongoDB and ClickHouse.
- Manage and maintain workflows in Airflow.
Requirements
- 7+ years of experience as a Data Engineer.
- 5+ years of experience with Python, TypeScript, Node.js, Kafka.
- Strong understanding of data processing algorithms and principles.
- Hands-on experience with ClickHouse, Airflow, Amazon S3, Git, Docker.
- Solid understanding of Data Lake and Data Warehouse architectures.
- Experience working with large-scale data and query optimization.
- Ability to work collaboratively toward shared goals.
- Strong sense of ownership, responsibility, and proactivity.
- English level: B1+.
Tech Stack
- Airflow
- Docker
- ETL
- JavaScript
- Kafka
- MongoDB
- Node.js
- Python
- TypeScript
Benefits
- 31 days off
- 100% paid telemedicine plan
- Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
- English learning courses
- Relevant professional education
- Gym or swimming pool
- Co-working
- Remote working