Support Solutions Engineer (L5) - Data Platform, Online DataStores

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

About the Engineering Support Organization

The primary goal of the Engineering Support Organization is to empower Data Platform Engineering to scale customer support sustainably and effectively. Serving as the frontline resource for our engineering workforce, the team handles, troubleshoots, and resolves customer requests and issues. Moreover, the team concentrates on improving methods of work, advocating for customers, enhancing support tools, expanding platform product offerings, and advancing documentation and developer education.

Our Mission 

Deliver an excellent support experience to Netflix’s developer community. To advocate for our customers, follow through on issues and resolve them in a reasonable time. If blockers prevent immediate resolution, we communicate status and ensure there is visibility into why there is a delay. 

Provide insights, feedback and champion customer sentiment about the tools we support to our partners across Data Platform. Partner with PM and Engineering to track and maintain visibility into ongoing issues and communicate customer needs to ensure improving in these areas is prioritized.

Drive collaboration efforts to reduce product friction and increase usability so that Data Platform can build, deploy and deliver highly functional solutions for the Developer Community.

Our culture is unique, and we tend to live by our values, allowing you to do your best work and grow.

The Role 

We are looking for a Support Solutions Engineer with a passion for Online Datastores and tooling, customer service, and automation. You will be responsible for monitoring and handling our customers’ requests, troubleshooting, solving issues, automating support needs, developing runbooks, improving and maintaining support tools, understanding our product offerings, and continuously looking for ways to improve the engineering support experience.

Our ideal team member has first-hand experience working in customer-facing engineering support roles, writing and building comprehensive self-service knowledge bases, and possesses knowledge of infrastructure, internal tooling, platforms, and cloud computing. You are excellent at understanding and solving complex, ambiguous problems and constantly seek improvement. As an Engineer in this role, we need a candidate who can understand our complex offerings on a technical level, be hands-on in the development of our support automation tooling, and recommend product and operational improvements based on customer interactions.

Location

This role is based in Warsaw. Since this role supports both US/Canada and local Poland teams, the required working hours are 12pm to 8pm local time.

What you’ll need to be successful:

• You are skilled in providing superior customer support across a complex organization, ideally as part of a central team.

• You are passionate about customer experience

• You are a data-driven decision-maker

• You have excellent written and verbal communications skills and appreciate the importance of comprehensive documentation.

• You have strong collaboration skills and experience working with cross-functional teams to drive customer feedback and closing the loop on high friction points.

• Experience in design, implementation, and maintenance of scalable NoSQL datastore solutions

• You have experience with scripting/automation, APIs, development, automation tools, Git cli and are comfortable with Java or Python

• You have experience operating and using one (or more) of the following:

  • Elasticsearch - Familiarity with other components of the Elastic Stack, such as Kibana

  • KeyValue datastores (e.g. Cassandra)

  • Caching systems like Redis and Memcached

  • RDBMS (Aurora/RDS, CockroachDB)

  • AWS (EC2, S3, Route53, Autoscaling)

• You under