Lead Data Engineer(Partner Company Role)
FYST · Ukraine
Skills in this posting
Benefits
The posting
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.
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.
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
Originally posted on Himalayas
The PivotHop read
- What a data engineer actually earnsmedian, seniority, by country
- What data engineers do insteadevery measured route out
- Data Architect → Data Engineer47% readiness
- Data Analyst → Data Engineer28% readiness
- All open data engineer rolesthe full board
Where these skills also reach
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