Data Engineer

OverviewWe are looking for an experienced Data Engineer with at least 5 years of professional experience and a solid technology background using Java or Python as a primary language.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, 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.About the companyRevup Payments 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 offer 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.Key ResponsibilitiesDesign, build, and maintain scalable data pipelines in AWS to support operational and analytical use casesDefine 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 sourcesDefine data schemas, partitioning strategies, and access patterns optimized for performance and costCollaborate with development and analytics teams to understand and fulfill the company's data requirementsImplement monitoring and alerting mechanisms to ensure the integrity and availability of data streamsWork with the operations team to optimize the performance and efficiency of the data infrastructureAutomate management and maintenance tasks of the infrastructure using tools such as Terraform, Ansible, etcStay updated on best practices and trends in data architectures, especially in the realm of real-time data ingestion and processingMonitor and troubleshoot data workflows using tools such as CloudWatch, Prometheus, or Datadog—proactively identifying bottlenecks, ensuring pipeline reliability, and handling incident response when necessaryEnsure data quality and performanceDefine and test disaster recovery plans (multi-region backups, Kafka replication, Snowflake Time Travel) and collaborate with security/infra teams on encryption, permissions, and complianceRequirementsBachelor's degree in Computer Science, Software Engineering, or a related field (equivalent experience is valued)At least 3 years of programming experience with Java / PythonExperience in data engineer design and delivery with cloud based data Warehouse technologies, in particular Snowflake, or Redshift, BigQueryExperience in a wide range of DB technologies such as, DynamoDB, Postgres, and MongoDevelopment with cloud services, especially Amazon Web ServicesDemonstrable experience in designing and implementing data pipeline architectures based on Kafka in cloud environments, preferably AWSDeep understanding of distributed systems and high availability design principlesExperience 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 StreamingExcellent communication and teamwork skillsAbility to independently and proactively solve problemsExtra bonus ifExperience with other streaming platforms such as Apache Pulsar or RabbitMQExperience in DBA administration and performance tuning standardsFamiliarity with data lake architectures and technologies such as Amazon S3, Apache Hadoop, or Apache DruidRelevant certifications in cloud platforms such as AWS (optional)Understanding of serverless architecture and event-driven systemsPrevious professional experience in FinTech / online payment flowsExperience with data visualization tools like Tableau, PowerBI, or Apache SupersetUnderstanding of machine learning concepts and frameworks for real-time data analyticsPrevious experience in designing and implementing data governance and compliance solutionsBenefitsCompetitive compensation package, including health insurance and performance bonusesOpportunities for professional growth and development in a high-growth fintech environmentCollaborative and innovative culture focused on making an impact in the global payments industryFlexible working environment with support for work-life balanceFull remote work#J-*****-Ljbffr