Vacantes en Valencia, España

About Us

Macropay is a fintech leader in payment orchestration, providing businesses with seamless access to global payment solutions for over four years. Specializing in revenue optimization, we oer card processing and alternative payment methods enhanced by smart routing, fraud prevention, and an intuitive dashboard. Backed by a team of payment and fraud experts, our all-in-one platform is designed to maximize revenue, reduce costs, and improve the payment experience—all through a single API integration.

About the role

In this role, you will design, build, and maintain scalable, secure, and high-performance cloud-based data pipelines to support real-time and batch analytics within our payments platform. You will work closely with product owners, data scientists, and cross-functional engineering teams to translate business requirements into robust data models and ETL / ELT workflows. Your day-to-day work will include architecting and implementing Kafka-based streaming pipelines, processing event streams and orchestrating data ingestion and transformation jobs on AWS. You will leverage Snowflake as our central data warehouse.

Key Responsibilities :

• Define and enforce best practices for data ingestion, cataloging, and lineage across our cloud infrastructure (AWS S3, Glue, EMR, Lambda, etc.).
• Develop and maintain real-time processing applications using Kafka (Producers, Consumers, Streams API) or similar technologies to aggregate, filter, and enrich streaming data from multiple sources.
• Collaborate with development and analytics teams to understand and fulfill the company's data requirements.
• Develop ecient and scalable data pipelines for data transformation and enrichment.
• Implement monitoring and alerting mechanisms to ensure the integrity and availability of data streams.
• Work with the operations team to optimize the performance and eciency of the data infrastructure.
• Automate management and maintenance tasks of the infrastructure using tools such as Terraform, Ansible, etc.
• Stay updated on best practices and trends in data architectures, especially in the realm ofreal-time data ingestion and processing.
• Monitor and troubleshoot data workflows using tools such as CloudWatch, Prometheus, or Datadog—proactively identifying bottlenecks, ensuring pipeline reliability, and handling incidentresponse when necessary.
• Ensure data quality and performance
• Define and test disaster recovery plans (multi-region backups, Kafka replication, Snowflake Time Travel) and collaborate with security / infra teams on encryption, permissions, and compliance

Requirements

Extra bonus if :

Benefits