We are seeking an experienced Backend Engineer to join the team responsible for ETL re-platforming and implementing multi-tenant, event-driven architecture. The ideal candidate has deep hands-on experience with microservices, data processing, distributed data flows, and Kubernetes-based deployments in cloud environments.
This role involves designing and developing backend services, ETL/ELT pipelines, integrating real-time messaging, ensuring high observability standards, and collaborating with platform, data, and DevOps teams.
Technical Requirements10+ years of backend software development experience.
5+ years of hands-on experience with Python OR Ruby
1+ years of professional experience with Go (Golang).
Practical experience designing or maintaining microservices.
Experience with event-driven messaging systems such as Apache Pulsar (preferred), Kafka, or NATS.
Data
Experience with ETL/ELT pipelines and data processing.
Experience with at least one Data Lake Stack.
Proficiency with SQL, proven experience with SQL, and No-SQL databases.
Cloud & Deployment
Hands-on knowledge of Kubernetes, including deployments, scaling, and configuration.
Practical experience with Kubernetes operators, CRDs, and Helm.
Understanding cloud CI/CD systems and delivery pipelines (GitHub Actions).
Nice to Have
Experience with C/C++ (networking, concurrency, high-performance systems).
Experience with Apache Iceberg, Apache Polaris, and the Trino stack.
Experience designing and building multi-tenant data architectures.
Experience implementing observability stacks (Prometheus, Grafana, Open Telemetry).
Familiarity with cloud platforms (AWS, GCP, or Azure).
Design, implement, and maintain Go microservices powering the system core.
Participate in the system to re-design, ETL for re-platforming, and integration with existing services.
Working with Apache Pulsar to support real-time data distribution.
Working with Apache Polaris catalogues and Trino queries.
Ensure observability and reliability through logging, metrics, and tracing.
Deploy and maintain services in Kubernetes environments across cloud platforms.
Contribute to the Data Engineering, Platform, and DevOps areas.
Participate in technical discussions, code reviews, and performance optimizations.
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