Customer Support Engineer

Jobgether; United States; Remote; USD 95,000 - 125,000; Full time

Benefits offered by this job

Annual salary 95,000–125,000 USD

Employee stock option grants

Flexible PTO

Remote work within the United States

Job summary

Jobgether is seeking a Customer Support Engineer for the United States to assist enterprise customers with data infrastructure and analytics platforms. You will troubleshoot complex issues across Linux, cloud environments, and distributed systems, coordinating with engineering and sales teams to deliver timely solutions.

The role emphasizes open-source tech, strong communication, and a hands-on problem-solving approach in a fast-paced, remote-friendly setting within the Pacific Time Zone.

Qualifications

• Experience deploying, troubleshooting, and debugging complex software systems in enterprise support.
• Familiarity with big data ecosystems and distributed data processing technologies.
• Understanding of cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Docker and Kubernetes in deploying distributed applications.
• Practical Linux skills for investigating system behavior and logs.
• Understanding security principles, OAuth2, LDAP, SSL/TLS.
• SQL knowledge for data access and queries.
• Exposure to Java, Python, Bash, and SQL.

Responsibilities

• Respond to and resolve customer inquiries related to enterprise and cloud-based data platforms via chat, email, and live sessions (SLAs).
• Diagnose and investigate complex technical issues across configuration, security, integrations, and distributed clusters.
• Analyze problems across Linux, cloud, containerized apps, and distributed data systems to identify root causes.
• Coordinate with engineering to investigate escalations and communicate progress to customers.
• Explain complex concepts clearly and manage customer expectations professionally.
• Contribute to customer-facing documentation and self-service knowledge resources.
• Collaborate with pre-sales, post-sales, and engineering teams to align support efforts.
• Engage in technical training and knowledge-sharing to deepen distributed data expertise.
• Identify recurring issues and suggest improvements to support processes and troubleshooting.

Skills

Technical Support Experience

Distributed Data Tech

Cloud Infrastructure

Docker

Kubernetes

Linux Administration

Security & Auth

DBMS & SQL

Programming & Scripting

Communication Skills

Problem Solving

Customer Orientation

Collaboration

Learning Mindset

Timezone: Pacific

Tools

Docker

Kubernetes

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Customer Support Engineer based in the United States. Join a technically driven team helping enterprise customers unlock the full potential of their data infrastructure and analytics platforms. As a Customer Support Engineer, you will troubleshoot complex technical challenges and help customers maintain reliable, secure, and efficient data environments. You will support enterprise and cloud-based products, resolving issues related to configuration, integrations, security, and distributed systems. Working directly with customers through chat, email, and live calls, you will deliver timely solutions while maintaining high service standards. You will collaborate with engineering, pre-sales, and post-sales teams to investigate escalated issues and continuously improve the customer experience. This role offers an opportunity to deepen your expertise in open-source data technologies, cloud platforms, and large-scale distributed systems. Ideal for a curious, customer-focused technical professional, this position combines hands‑on problem‑solving, continuous learning, and cross‑functional collaboration in a fast‑paced environment.

Accountabilities

• Customer Technical Support: Respond to and resolve customer inquiries related to enterprise and cloud-based data platforms through chat, email, and live troubleshooting sessions, meeting established service-level agreements (SLAs).
• Troubleshooting and Issue Resolution: Diagnose and investigate complex technical issues involving configuration, security, authentication, authorization, integrations, database connectivity, and distributed cluster environments.
• Technical Investigation: Analyze problems across Linux environments, cloud infrastructure, containerized applications, and distributed data systems to identify root causes and recommend effective solutions.
• Escalation Management: Coordinate with engineering teams to investigate and resolve advanced technical issues, manage escalations, communicate progress, and ensure customers receive appropriate and timely support.
• Customer Communication: Serve as a trusted technical point of contact, explaining complex technical concepts clearly, setting appropriate expectations, and maintaining professional, responsive customer relationships.
• Knowledge Base Development: Contribute to customer-facing documentation, troubleshooting guides, and self‑service knowledge resources to help users resolve common issues independently.
• Cross-Functional Collaboration: Partner with pre-sales, post-sales, engineering, and other internal teams to align technical support efforts, share insights, and improve customer satisfaction.
• Continuous Learning: Participate actively in technical training, team knowledge-sharing sessions, and professional development activities to strengthen expertise in distributed data technologies and evolving customer needs.
• Service Quality Improvement: Identify recurring technical issues, document findings, and recommend improvements to support processes, troubleshooting practices, and the overall customer experience.

Requirements

• Technical Support Experience: Experience deploying, troubleshooting, and debugging complex software systems, preferably in enterprise customer support, technical support engineering, systems engineering, or a related technical role.
• Distributed Data Technologies: Familiarity with big data ecosystems and distributed data processing technologies, including Hadoop, data lakes, and Apache Spark.
• Cloud Infrastructure: Understanding of cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
• Containers and Orchestration: Knowledge of Docker and Kubernetes, including their use in deploying, operating, and troubleshooting distributed applications.
• Linux and Systems Administration: Practical Linux skills and the ability to investigate system behavior, analyze logs, troubleshoot configuration issues, and diagnose performance or connectivity problems.
• Security and Authentication: Understanding of security principles, authentication and authorization mechanisms, LDAP, OAuth 2.0, and SSL/TLS.
• Database and Querying Skills: Familiarity with database management system (DBMS) concepts and SQL, including the ability to investigate data access and query-related issues.
• Programming and Scripting: Exposure to Java, Python, Bash, and SQL. Experience navigating a complex Java codebase or using scripting to automate troubleshooting is an advantage.
• Communication Skills: Strong written and verbal communication skills, with the ability to explain technical issues clearly to customers with varying levels of technical expertise.
• Problem-Solving Ability: Analytical thinking, attention to detail, and a structured approach to diagnosing complex issues, identifying root causes, and developing practical solutions.
• Customer Orientation: A strong commitment to customer success, responsiveness, and delivering high-quality support while managing multiple inquiries and priorities.
• Collaboration and Adaptability: Ability to work effectively across technical and business teams in a fast‑paced, evolving environment.
• Learning Mindset: Curiosity about distributed systems, open‑source technologies, and new technical approaches, along with the motivation to continuously develop technical expertise.
• Location and Time Zone: Ability to support customers and collaborate with colleagues during Pacific Time Zone business hours.

Benefits

• Competitive Compensation: Annual salary ranging from $95,000 to $125,000, depending on qualifications, experience, and work location.
• Equity Compensation: Employee stock option grants, providing an opportunity to participate in the organization's long-term growth.
• Flexible Paid Time Off: Access to flexible paid time off to support rest, personal commitments, and work-life balance.
• Comprehensive Benefits: Access to a competitive total rewards package designed to support employees' professional and personal well-being.
• Remote Work Environment: Opportunity to work remotely within the United States, with a focus on Pacific Time Zone alignment.
• Career Development: Opportunities to learn from experienced technical professionals, expand expertise in distributed data systems, and take ownership of career growth.
• Innovative Technology: Hands‑on exposure to enterprise data platforms, cloud technologies, open standards, and modern analytics infrastructure.
• Collaborative Culture: An inclusive environment that values diverse perspectives, authentic communication, shared ownership, and continuous improvement.
• Meaningful Customer Impact: Opportunity to solve challenging technical problems and help enterprise customers improve the reliability, accessibility, and performance of their data environments.

We appreciate your interest and wish you the best!