Customer Success Engineers at Databricks serve as the trusted technical advisors for our customers. They improve value, offer advice, and grow accounts. At Databricks we work on some of the most complex distributed processing systems and our customers challenge us with interesting new big-data processing requirements. As the complexity grows for both us and our customers, we are looking to our Customer Success Engineers to strategize and lead customers to solutions. This is done with use case discovery, Databricks evangelism, and oftentimes teaching the product to new users. A Customer Success Engineer must be ready to work and have technical discussions with data scientists and engineers, then demonstrate the value of Databricks in business discussions with company executives. The goal is to help our customers to become successful and enthusiastic Databricks champions. Armed with customer insight, a Customer Success Engineer must work with the sales, product, engineering, support, and marketing teams.
The impact you will have:
You will manage the customer lifecycle for an assigned number of accounts. You will need to build relationships with them and engage by presenting product roadmaps and executive briefings, running QBRs, managing escalations, and conducting regular status calls.
Learn and become a Databricks + Spark expert! Customers will look to you for advice and expertise.
Strategize and identify new use cases to grow accounts. Find areas where Databricks can provide the most value to increase renewals.
Engage with the product team to guide customer requests and establish our roadmap.
Work with the technical support team and other core Databricks teams to ensure that customer requests and escalations are resolved.
Identify and achieve targets on renewal rates, customer satisfaction, expansions, upsells, and new opportunities in assigned accounts.
Develop Databricks champions and produce customer references for the marketing team.
Be a true proponent of customer advocacy.
You will inspire, mentor and coach other team members.
What we look for:
Minimum 4 years experience working in customer-facing technical roles (in Customer Success, consulting, or related discipline)
Experience at a SaaS company or with cloud architectures
Languages: Python, or SQL
Familiarity with the end-to-end data analytics workflow
Experience with databases and data warehousing
Problem solving skills, those that apply to a ‘big data’ environment
Some travel may be involved depending on customer’s needs.
Bachelor’s degree in computer science or related field.
Nice to have:
Domain experience with Manufacturing, Retail, Health and Life Sciences, Communication and Media experience
Fluency with cloud services such as AWS or Azure
Fluency with distributed streaming platforms (Kafka, Kinesis)
Experience working with large-scale data processing services (Hadoop)
Background in machine learning or working with ML tools and services
Verbal and written proficiency with French language
Flexible time off
Paid parental leave
Annual personal development fund
Work headphones reimbursement
Employee Assistance Program (EAP)
Business travel accident insurance
Mental wellness resources
Read MoreJobicy’s Feed