Вакансия Junior Data Engineer

Skills

• Python
• ETL
• SQL
• AirFlow
• Dagster
• Prefect
• Kubernetes
• Apache Spark
• Apache Flink
• Kafka
• dbt
• Delta Lake
• Iceberg
• FastAPI

Описание вакансии

We are a Data Engineering Service that provides the collection, preprocessing, and storage of analytical data for data-driven decision-making, including the company's products and process improvements via automation, all types of data analysis, and machine learning.
We are currently looking for a Junior Data Engineer who is enthusiastic about learning and ready to work in a dynamic data environment.

In this role, you will:

• Develop and maintain data pipelines (Data Streaming Processors, ETL for third-party data sources) and data tools (Anomaly Detection System, AB testing system, etc.) for internal clients with the help of a team
• Implement and propose technical solutions based on already used in service to cover all acceptance criteria and other team agreements (e.g, tech documentation, tests, NFRs, etc.)
• Support team in reacting to issues and failures by fixing them according to service agreements and priorities
• Develop and maintain documentation, code, and business logic according to service requirements with the team's help
• Communicate with the service team to clarify implementation details and edge cases, specify input or missing data and possible use cases/flows
• Take part in service duty procedures

Skills you’ll need to bring:

• Experience with Python ETL pipelines
• Strong SQL skills (complex joins, window functions, bulk-loading into a data warehouse)
• Experience with orchestration tools like Apache Airflow or similar: Dagster, Prefect
• Experience diagnosing pipeline issues (Airflow logs, warehouse errors, Kubernetes diagnostics, support‑ticket triage)
• Experience consuming third‑party APIs (authentication, pagination, error handling)
• Knowledge of data engineering fundamentals (data modeling, warehousing concepts, ETL best practices, data quality fundamentals)
• Knowledge of cloud computing fundamentals (computational resources, reading/writing to storage, basic IAM)
• At least an Intermediate level of English & fluent Ukrainian

As a plus:

• Experience with Apache Big Data ecosystem (Spark, Flink, Kafka, etc.)
• Knowledge of dbt
• Knowledge of Open-table formats (Delta Lake, Apache Iceberg)
• Knowledge of data lakehouse concepts
• Knowledge of how to implement APIs (preferably FastAPI)