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 Requirements

• 10+ years of backend software development experience.

• 5+ 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).

Responsibilities

• 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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