Description:

Design target-state data architecture: Postgres CDC → Kafka → Snowflake → client-facing data products.
Own tooling decisions across ingestion, orchestration, transformation, and quality layers.
Implement CDC-based ingestion from PostgreSQL services using Debezium or equivalent.
Build streaming and near-real-time pipelines with defined SLAs.
Establish a data quality control layer: checksums, reconciliation, schema validation, anomaly detection, and alerting.
Define quality checkpoints across the full pipeline.
Define and enforce data contracts with service-owning teams for core entities.
Build the external data delivery layer for financial settlement and client analytics.
Design tenant separation and implement replay/reload mechanisms for failure recovery.
Start hands-on, then hire and grow a small data engineering team with a pragmatic roadmap.

Requirements:

5+ years in data engineering with end-to-end ownership of production pipelines.
Hands-on experience with Snowflake, PostgreSQL CDC (Debezium preferred), and Kafka.
Solid AWS experience — S3, RDS, Aurora, and cloud data infrastructure.
Data quality engineering mindset: monitoring, reconciliation, lineage.
Comfortable defining data contracts and driving requirements with backend engineering teams.
Technical leadership experience: project ownership, cross-team alignment, delivery under constraints.
Kubernetes, Airflow/Prefect/Dagster, and dbt are strong pluses.
Payments domain knowledge is a strong plus.
Familiarity with gRPC, RabbitMQ, and reading Go/Python service code is expected.
English language skills at the B2 level and fluent Russian language.

Opportunity to contribute to the growth of a leading fintech company.
Career prospects with a focus on employee growth.
Work with passionate coworkers.
Competitive compensation with yearly performance reviews.
Remote work flexibility.
20 days of vacation, bank holidays, sick leaves, and an additional birthday day off.

Skills

Benefits