Senior Backend (Go) Engineer

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 re‑design, ETL for re‑platforming, and integration with existing services.
• Work with Apache Pulsar to support real‑time data distribution.
• Work 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.