Designing and optimizing the architecture of the Data Core platform for high scalability, availability, and performance.
Building and improving data pipelines, orchestration frameworks, and monitoring solutions to support real-time analytics and mission-critical workloads.
Leading initiatives in observability, automation, and system resilience (SRE), ensuring uptime and stability for customers in production.
Driving performance tuning across distributed systems and data services (SQL/NoSQL, message queues, caching, etc.).
Collaborating cross-functionally with cloud, product, and DevOps teams to enhance CI/CD pipelines and deployment automation.
Mentoring junior engineers and contributing to best practices around reliability, testing, and data operations.
Championing cloud-native engineering across Azure and GCP environments.
Requirements
5+ years of experience in backend or data engineering
Strong expertise in Java (or a JVM-based language) and data platform technologies (e.g., Kafka, Spark, PostgreSQL, Elastic, Redis)
Deep understanding of cloud infrastructure (Azure and/or GCP) and containerized environments (Kubernetes, Docker)
Proven experience in observability, automation, and system reliability (SRE, Prometheus, Grafana, Terraform, etc.)
Strong grasp of CI/CD pipelines, DevOps workflows, and Infrastructure as Code
Excellent analytical, problem-solving, and debugging skills across complex systems.
A collaborative mindset and the ability to lead by example in a fast-paced, innovative environment.
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