Employment Status: Contract - 4 months **with high possibility of converting to probationary, depending on client's needs**

Working hours: US Eastern (8 PM to 5 AM MNL)

Work set-up: 100% WFH/Hybrid

WHAT IS YOUR ROLE:

As a Customer Support Engineer Lead, you will ensure our Customers are happy and successful by providing and leading a best-in-class support experience. You will be the leader of a Level 2 Customer Support Engineering team, responsible for resolving escalated customer inquiries and incidents for the SaaS platform. Customer Support Engineers communicate directly with customers to help resolve their requests, triage, troubleshoot and resolve platform incidents, and participate in an On-Call Rotation to ensure 24/7 support coverage. You will collaborate with Professional Services, Customer Success, Product, and Engineering to ensure timely and high-quality resolution of customer requests and incidents. Your impact will be felt throughout the company, and visible both internally and externally.  As a critical team in a growing startup, you will also help the team continuously improve tools and processes to support our growing customer base.

WHAT WILL YOU DO:

• Provide guidance and leadership to the customer support engineering team, ensuring efficient operations and a high level of customer satisfaction.
• Train, mentor, and coach team members to enhance their technical and customer service skills.
• Drive high customer satisfaction by understanding, troubleshooting and resolving customer requests and incidents
• Monitor, triage and resolve technical incidents and escalations that arise in the omnichannel support queue, meeting required SLAs
• Use existing troubleshooting guides (TSGs) and standard operating procedures (SOPs) to establish root cause for queries and provide a customer-facing root cause assessment
• Provide how-to’s, best practices, and consultative suggestions to support customers in enabling value-add use cases
• Participate in on call rotation, ensuring 24/7 coverage for escalated incidents
• Balance multiple tasks with varying priorities and urgencies
• Monitor and ensure the health of the SaaS platform
• Collaborate with Product, Engineering, Customer Success, Professional Services, and Level 1 Support to ensure quick resolution to customer challenges
• Develop an understanding of the CXHub, including how the CXHub drives value for customers, and how it fits in the customer CX/martech stacks

• Bachelor's degree or higher in Computer Science or related field
• 3-5 years of experience leading a support engineering team
• +5 years experience in customer support engineering
• 3-5 years of experience in SQL, python or similar programming languages, command line operations in a Linux environment
• 3-5 years of experience and exposure to APIs (REST, SOAP)
• Enthusiasm for working with customers through various channels to help drive customer satisfaction
• Strong problem-solving and analytical skills
• Clear communication and great collaboration skills
• Strong knowledge of algorithms, data structures, design patterns, networking and operating systems.
• Knowledge of the Software Development Life Cycle
• Understanding of Monitoring & Alerting tools (Datadog, Pagerduty, Alert Manager, etc)

• SSS
• Pag-ibig
• Philhealth
• HMO on day one
• 13th month pay
• Paid incentive leaves
• Personal time-offs (PTOs)
• Sick leave

Strategic Analytics is a dynamic, growing team at Arch.  The team develops innovative predictive models and analytical tools to improve profitability and growth.  This position will support the technical implementation of predictive models and analytical tools of the Strategic Analytics team.  The position requires strong Python and SQL experience, as well as monitoring and maintence support experience.  The role is for an individual who is open to exploring and implementing new technology in Azure and Databricks, as the team is dynamic and the technology needs and requirements are fluid and will evolve over time.

• Develop and maintain Databricks Notebooks and Azure Data Factory Pipelines
• Develop libraries using Python
• Develop batch data workflows for analytics-driven solutions
• Build analytical tools and expand capabilities to improve monitoring of predictive model applications and processes
• Use SQL, Python and Snowflake to explore and understand underlying data, and suggest improvements for monitoring, performance, and best practice
• Document technical workflows and monitoring processes
• Collaborate with project stakeholders and other developers
• Code deployment using GitHub
• Contribute and enforce evolving best standards and practices