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# Lead Data Engineer

- **Company:** Búsqueda Avanzada
- **Location:** Barcelona, Spain (Remote available)
- **Salary:** €60,000.0 - €65,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Cloud Database, Information Engineering, Python (Programming Language), PostgreSQL, RabbitMQ, Snowflake, Debezium, Kubernetes, Apache Kafka, Data Delivery, Grpc
- **Published:** July 20, 2026
- **Apply:** https://www.adzuna.es/contact-us.html

## About the 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.

## Description

+ 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.


## Related Videos

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- [Beyond Kafka & RabbitMQ: Why NATS is the Future of Microservices Messaging](https://www.wearedevelopers.com/videos/1646-beyond-kafka-rabbitmq-why-nats-is-the-future-of-microservices-messaging)
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- [Developing ASP.NET Core Microservices with Dapr: A practical guide](https://www.wearedevelopers.com/videos/1528-developing-asp-net-core-microservices-with-dapr-a-practical-guide)
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