Data Engineer
Core
Design and build event-driven, real-time data pipelines on ClickHouse, Google Cloud, and Airflow to power dashboards and self-serve analytics for payments and billing.
Role type
Senior Data Engineer (Real-time Financial Analytics)
Builds
Event pipelines, optimized datasets, and low-latency data products for product, finance, risk, and operations teams.
Domain
Fintech / Payments / Subscriptions
Deliverable
production ML models | product features | dashboards & analysis
Required skills
ClickHouse (MergeTree, projections, materialized views), Event-driven pipelines (Kafka/PubSub/Kinesis), Google Cloud (Pub/Sub, GCS, BigQuery, Cloud Run/GKE), Apache Airflow, Advanced SQL, Python for data engineering, Data quality observability, Financial data modeling
Preferred skills
Tinybird, dbt, Dataflow/Beam/Spark, Terraform/IaC, Docker/Kubernetes, Risk/fraud analytics, A/B test infrastructure
Technologies
ClickHouse, Google Cloud Platform, Airflow, Kafka, Pub/Sub, Kinesis, BigQuery, GCS, Cloud Run, GKE, Tinybird, dbt, Terraform, Docker, Kubernetes
Responsibilities
Design and build event-driven, real-time data pipelines; Optimize ClickHouse schemas and queries; Model core financial datasets for payments and subscriptions; Own data quality and observability; Investigate anomalies and perform root-cause analysis; Partner with Backend/Platform on event schemas; Document logic and build internal tooling
Seniority
Senior, hands-on IC
