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AI Summary
Design and implement a target-state data architecture using Postgres CDC, Kafka, and Snowflake to build client-facing data products. Lead the development of data quality layers and data contracts while gradually hiring and growing a data engineering team.
We're looking for the right person to build that foundation from the ground up.
This is a hands-on leadership role with real ownership: you'll shape how data is collected, structured, and delivered — and grow a team around you as the function matures.
This is a hands-on leadership role with real ownership: you'll shape how data is collected, structured, and delivered — and grow a team around you as the function matures.
WHAT YOU'LL BE WORKING ON
- Design the 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 (RDS, Aurora, EC2, K8s operator) using Debezium or equivalent.
- Build streaming and near-real-time pipelines with defined SLAs.
- Build a data quality control layer: checksums, reconciliation, schema validation, anomaly detection, and alerting.
- Define quality checkpoints across the full pipeline — from source capture through Snowflake to client delivery.
- Define and enforce data contracts with service-owning teams for core entities: transaction, merchant, settlement, and processing status.
- Build the external data delivery layer: financial settlement, transaction status, processor reconciliation, and client analytics.
- Design tenant separation and implement replay/reload mechanisms for failure recovery.
- Start hands-on, then gradually hire and grow a small data engineering team as the function matures.
Build a pragmatic roadmap with concrete deliverables at 3, 6, and 12 months.
WHAT YOU NEED TO SUCCEED IN THIS ROLE
- 5+ years in data engineering with end-to-end ownership of production pipelines.
- Hands-on 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 — settlement, transaction lifecycle, processor integrations — 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.
WHAT WE OFFER
- An opportunity to make something great even greater, you can be the reason why we grow, develop, and become the best fintech company on the market!
- Career prospects - we are young, we have huge ambitions, and it is important that our employees grow with us
- Work with coworkers who are passionate about their business
- Compensation that will fully correspond to the competence and knowledge, with yearly performance reviews
- Remote work
- 20 days of vacation time; bank holidays; sick leaves; additional birthday day off
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