E-Importer / Integrations and data synchronization
Automated data synchronization from 1C
A backend system for automated export and synchronization from 1C to a web application.
Product Designer and Full-stack Developer
Task
Products, categories, attributes, and related records arrived from 1C and external sources in different formats. They needed to be synchronized with the web application automatically.
How data exchange works
The import flow is split into ingestion, validation, processing, and publishing. Records are normalized before persistence.
Kafka carries events, PostgreSQL stores primary data, and Redis keeps transient processing state.
Failures and reprocessing
Background jobs use retries, timeouts, and execution statuses. Duplicate-processing protection prevents the same export from creating duplicate records.
Job statuses and structured logs show the stage where a failure occurred.
Import interface
I designed the interface structure for starting an export, tracking statuses, reviewing errors, and reprocessing a job.
I connected interface states and messages to backend processing stages so a problem can be located without manually checking the entire pipeline.
My responsibilities
Data ingestion, transformation, and synchronization between 1C, PostgreSQL, and the website.
Parsers and integration services for inconsistent input formats.
Background jobs, retries, timeouts, and status tracking.
Data normalization, migrations, and structured logging.
Stack
- Python
- FastAPI
- PostgreSQL
- SQLAlchemy
- Kafka
- Redis
- Docker
