Data Engineer

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 1. Bachelor's degree in Computer Science, Software Engineering, or a related field (equivalent experience is valued). 2. We are looking for an experienced Data Engineer with 5+ years of professional experience and a solid technology background using Java or Python as a primary language. 3. 3+ years of programming experience with Java / Python 4. Experience in data engineer design and delivery with cloud based data Warehouse technologies, in particular Snowflake, or Redshift,BigQuery 5. Development with cloud services, especially Amazon Web Services 6. Demonstrable experience in designing and implementing data pipeline architectures based on Kafka in cloud environments, preferably AWS. 7. Deep understanding of distributed systems and high availability design principles. 8. Experience in building and optimizing data pipelines using technologies like Apache Kafka, Apache Flink, Apache Spark, etc., including real-time processing frameworks such as Apache Flink or Apache Spark Streaming. 9. Excellent communication and teamwork skills. 10. Ability to independently and proactively solve problems. Extra bonus if : 11. Experience with other streaming platforms such as Apache Pulsar or RabbitMQ. 12. Familiarity with data lake architectures and technologies such as Amazon S3, Apache Hadoop, or Apache Druid. 13. Relevant certifications in cloud platforms such as AWS (optional). 14. Understanding of serverless architecture and event-driven systems 15. Previous professional experience in FinTech / online payment flows 16. Experience with data visualization tools like Tableau, PowerBI, or Apache Superset. 17. Understanding of machine learning concepts and frameworks for real-time data analytics. 18. Previous experience in designing and implementing data governance and compliance solutions. Benefits 19. Competitive salary and comprehensive benefits package. 20. Opportunity to shape HR strategy for a global, innovative fintech company. 21. Professional development opportunities and resources. 22. A collaborative, inclusive, and dynamic work culture. 23. Full Remote Work. #J-18808-Ljbffr

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