Responsibilities
The core responsibility of a Support Engineer is to support our customers at every turn in the company`s journey by providing answers to product questions, sharing best practices, and debugging technical issues. You'll also develop your technical skills, collaborate with our Product team to improve our product, learn product analytics, and mentor new team members.
Become a product expert – you will help users understand our reports and features, help them use our APIs and SDKs, share best practices, and resolve account issues.
Respond to customer inquiries via Zendesk email, chat, Slack, and phone calls.
Investigate and document bugs and feature requests to share with our Product and Engineering teams.
Provide feedback regarding internal support processes, product functionality, and customer education resources to improve the customer experience.
Shape the product by regularly working closely with PMs, engineers, and designers to incorporate customer learnings into change.
We're Looking For Someone Who Has
Experience providing customer facing SAAS support (in customer support, professional services, technical account management or similar).
Ability to communicate technical concepts effectively in a clear, friendly writing style.
Excellent problem-solving and analytical skills.
Programming experience, understanding of web & mobile technologies, and interacting with APIs.
Experience with debugging and collaborating with engineering to resolve complex technical issues, especially with JavaScript, Python, or mobile technologies.
Ability to be resourceful and resilient when faced with ambiguity and new challenges.
Dedication to developing expertise in a complex and constantly evolving product.
Interest and aptitude to develop technical skills and learn new technologies.
Experience providing SLA based support and/or dedicated support to strategic customers.
Speak Hebrew and fluent English.
Bonus Points
Experience with Mixpanel or other analytics tools.
Familiar with databases and cloud data warehouses like Google Cloud, Amazon Redshift, Microsoft Azure, Snowflake, Databricks, etc.
Familiar with product analytics implementation methods like SDKs, Customer Data Platforms (CDPs), Event Streaming, Reverse ETL, etc.
