Position Overview
As a Customer Success Technical Engineer, you’ll ensure our clients get maximum value from Ververica’s Unified Streaming Data Platform (powered by the VERA engine). You’ll be the primary technical advocate—troubleshooting both platform-level behaviour and customers’ stream-processing jobs, guiding best practices from onboarding through mission-critical operations.

Key Responsibilities

• Customer Support: Serve as the main point of contact for technical inquiries and incidents related to our platform and Flink-based pipelines.
• Issue Resolution: Diagnose, reproduce and resolve issues in a timely manner; own tickets from start to finish and maintain clear records in our support system.
• On-Call Support: Participate in a rotating on-call schedule outside standard business hours to deliver technical assistance and uphold SLAs for mission-critical deployments.
• Platform Guidance: Advise on packaging, deploying and managing containerized services (e.g., using Kubernetes) and configuration lifecycle. Guide customers on best practices for Flink job design and deployment models (e.g., on-prem Kubernetes, Cloud provider, Managed Flink, BYOC).
• Cloud Foundations: Leverage your understanding of cloud-native architectures and services (e.g., AWS, GCP, Azure) to guide customers in aligning Ververica Platform deployments with their existing compute, storage, networking and IAM setups—ensuring secure, resilient Flink operations.
• Troubleshooting: Empower users to diagnose and resolve issues by analyzing application logs, JVM and Flink metrics (e.g., from tools like Grafana, Kibana, Datadog), collecting performance data, and translating those insights into concrete recommendations for stable, high-throughput pipelines.
• Collaboration & Feedback: Partner with Product, R&D and Documentation teams to escalate complex issues, propose product enhancements and author knowledge-base articles.
• Customer Education: Create tutorials, sample projects and run technical workshops to accelerate customer success.

REQUIREMENTS

• Minimum 3 years of experience in a hands-on technical role such as Support Engineer, SRE, or Data Engineer, with at least 2 years in a customer-facing capacity.
• Java & JVM Expertise: Ability to read, reason about, and debug Java code. A solid understanding of the JVM is crucial for performance tuning and troubleshooting.
• Streaming & Big Data: Deep understanding of stream-and-batch processing architectures. Practical experience with streaming technologies like Apache Kafka, Pulsar, or Redpanda is essential.
• Kubernetes & Cloud: Strong conceptual knowledge and hands-on experience with containerization and orchestration. Familiarity with Docker, Kubernetes and Helm is essential, as our platform runs on it. Solid foundations in a major cloud provider (AWS, GCP, or Azure) plus IaC tooling (e.g., Terraform).
• SQL & Data Fundamentals: Proficiency in SQL for querying and analyzing streaming or batch data. Familiarity with data warehousing concepts, serialization formats (e.g., Avro, Protobuf), and data modeling trade-offs.
• Programming & DevOps: Proficiency in a general-purpose programming language (Java preferred), with experience in build/dependency management (e.g., Maven, Gradle) and CI/CD pipelines (e.g., ArgoCD/Flux).
• Distributed Systems: Comfortable explaining and troubleshooting distributed systems patterns (e.g., parallel execution, leader election, fault tolerance, state management, watermarks).
• Excellent Communication: A genuine passion for helping customers, with the ability to clearly explain complex technical concepts to both engineering and non-technical stakeholders.

Preferred Qualifications

• Industry certifications in cloud or DevOps disciplines.
• Experience with scripting or automation (e.g., Python, Shell).
• Background in open-source contributions or community support.
• Prior work in a remote/customer-focused environment.

• Customer Support: Serve as the main point of contact for technical inquiries and incidents related to our platform and Flink-based pipelines.
• Issue Resolution: Diagnose, reproduce and resolve issues in a timely manner; own tickets from start to finish and maintain clear records in our support system.
• On-Call Support: Participate in a rotating on-call schedule outside standard business hours to deliver technical assistance and uphold SLAs for mission-critical deployments.
• Platform Guidance: Advise on packaging, deploying and managing containerized services (e.g., using Kubernetes) and configuration lifecycle. Guide customers on best practices for Flink job design and deployment models (e.g., on-prem Kubernetes, Cloud provider, Managed Flink, BYOC).
• Cloud Foundations: Leverage your understanding of cloud-native architectures and services (e.g., AWS, GCP, Azure) to guide customers in aligning Ververica Platform deployments with their existing compute, storage, networking and IAM setups—ensuring secure, resilient Flink operations.
• Troubleshooting: Empower users to diagnose and resolve issues by analyzing application logs, JVM and Flink metrics (e.g., from tools like Grafana, Kibana, Datadog), collecting performance data, and translating those insights into concrete recommendations for stable, high-throughput pipelines.
• Collaboration & Feedback: Partner with Product, R&D and Documentation teams to escalate complex issues, propose product enhancements and author knowledge-base articles.
• Customer Education: Create tutorials, sample projects and run technical workshops to accelerate customer success