Office hour: Monday – Friday (9:00 AM – 6:00 PM)

Build and operate batch and near–real-time data pipelines integrating POS/ERP/WMS systems, e-commerce, marketing platforms, and external data sources.
Orchestrate and monitor workflows using Airflow, Prefect, or Dagster, ensuring defined SLAs and reliable incident management.
Design and maintain scalable schemas and core domain data models (Products, SKUs, Inventory, Sales, Suppliers, Warehouses).
Implement data quality frameworks including validation, reconciliation, freshness checks, and observability.
Develop, optimize, and maintain cloud data warehouses (BigQuery, Snowflake, or Redshift) with efficient dbt modeling.
Collaborate with ML/DS teams to deliver feature stores, training datasets, and production-ready model pipelines.
Establish and enforce data governance, security standards, documentation practices, and reusable data contracts/APIs.

4-6+ years of experience as a Data Engineer.
Strong SQL and solid Python skills (pandas/PySpark is a plus).
Hands-on experience with modern data warehouses: BigQuery, Snowflake, or Redshift.
Experience building production ETL/ELT pipelines using Airflow, Prefect, Dagster, dbt, or similar tools.
Strong understanding of data modeling (star/snowflake schemas, SCD, event modeling).
Experience with cloud platforms (GCP/AWS/Azure) and basic infra (Docker, CI/CD).
Good instincts for data quality, observability, and distributed system failure modes.
Clear communication and ability to collaborate across technical and non-technical teams.
Nice to have:
- Experience with retail/fashion/e-commerce data: inventory, sales, returns, promotions.
- Exposure to forecasting, time-series modeling, or ML pipelines.
- Startup experience, especially in early-stage environments.
- Familiarity with modern ELT stacks: Fivetran, Airbyte, or custom connectors.
- Experience building data products for analytics dashboards or embedded BI.

Annual salary review
100% salary during probation period.
5-days working week (Monday-Friday) – working hours are between 9 am to 6 pm.
12 days of annual leave
Flat organization and open communication
Friendly working environment and flexible working hours.
Great opportunity to develop career, collaborate with English speaking developers
Free parking at the building
13th salary, insurance.
The company organizes Team building every year (Free tickets for 01 relative to accompany)

Mid/Senior Data Engineer (English)

Job Description