Q & A with Toru Takahashi, Treasure Data’s Manager of Support Engineering

Q & A with Toru Takahashi, Treasure Data’s Manager of Support Engineering

At Treasure Data our customers are served by a dedicated team of Support Engineering ninjas. At the head of this team is Toru Takahashi, Support Engineering Manager. Managing a team that stretches the entire globe, from Mountain View to East Africa to Tokyo, Toru’s team is responsible for keeping Treasure Data customers empowered.

Q: How would describe your role at Treasure Data?

A: I’m the support engineering manager for Treasure Data Global Support.
Treasure Data provides a lot of features that require some amount of technical knowledge. The support team bridges the gap between our customers and product.

I also work on improving support processes and tools and on helping identify which features are missing for our customers.

Q: Tell me a bit about your technical background.

A: I studied Information Technology at the Nara Institute of Science and Technology. As a graduate student I studied Human-Robot Interaction for Elderly people living alone. After completing my studies, I joined the Big Data group at a systems integration company. I joined Treasure Data after that.

Q: What are some of the unique challenges that come with supporting a platform like Treasure Data as opposed to another traditional SaaS company?

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I do not have any prior experience working at other SaaS companies, so it is hard to say what the uniquely different challenges are. But one thing is surely unique: Treasure Data’s engineering team’s DNA is open source software (OSS). Our development style and tools are all OSS-based and almost all of our software (Fluentd, Embulk, Digdag, Presto, Hivemall, MessagePack, etc.) are developed, used, and published as OSS. As a consequence, the support team also needs to be familiar with the OSS development style.

Q: Treasure Data has over 100+ out-of-the-box connectors to allow ingestion and output of data to any database and SaaS platform. Our workflows allow the automation of data flows between those connectors and more. Yet, year after year, when customers are asked what they like most about us, the first answer is usually, “Great customer support,” followed by technical features. What are some of the things you do as support manager and as a support team to maintain such a great level of support?

A: We try to ensure our responses are quick and timely. We also ensure the team stays always up to speed with the changes on the platform to be able to provide deep and knowledgeable answers.

Q: From Japan to Mountain View to Amsterdam, Treasure Data has clients all over the globe, across continents, cultures and timezones. When providing support to such a diverse customer set, do you have to change or tweak your support style for each culture?

A: I am always trying to understand the differences between cultures. However, regardless of the culture, the single, least common denominator of great support is ‘doing’: “do what is needed, when it is needed, in the amount that is needed.”

Q: In your 5 years at TD, how would you describe the evolution of the Treasure Data platform?

A: Initially, Treasure Data was Hadoop as a Service, then we became Big Data as a Service, and only recently we pivoted towards being an enterprise customer data platform (CDP).

Q: How big is the support engineering team?

A: It’s a nimble team – we are 6 members at the moment. By the end of 2018, we will be 8 members from all over the world.

Q: Where are all the team members based?

A: US, Japan, Uganda and Korea.

Q: With so many connectors and platforms that TD needs to connect to, how do you manage to stay knowledgeable of so many disparate systems?

A: Treasure Data is based on a lot of OSS: I often read presentations and blog posts on the web. Afterwards I will try to use the tool myself and then write a blog about my experience using that particular tool with Treasure Data.

Q: What do you like most about working in support at TD?

A: I love the Treasure Data Platform as well as my co-workers. I believe Treasure Data really does help clients grow their businesses and I truly enjoy helping them get the most out of the platform.

Q: What is the toughest part about support at TD?

A: Our platform is built from multiple components and integrated with multiple external services. Every customer’s data pipeline is different and each customer can have multiple data pipelines, each integrating with several services. Investigating data issues and helping customers with questions about the data in their pipelines can be challenging. Tracing logs, troubleshooting data integrations, investigating data flows, and checking for possible bugs can be hard, but at the same time we enjoy the challenge and it’s very engaging.

Q: Treasure Data has refocused as a full fledged enterprise CDP. Do you foresee any impact on the Support Engineering Department?

A: In the past, the main type of customer the support team dealt with were engineers while now, the main users of CDP platforms are digital marketers. Therefore the customer’s technical background is completely different. I anticipate we will need to evolve our support style and processes to accommodate them.

Q: What are some of the technical skills required to do support at TD?

A: Knowledge of SQL, ETL and business intelligence tools is required as a minimum. Cloud experience (AWS, GCP, etc.) come also pretty handy.

Q: What are some of the qualities you look for when hiring a new support engineer?

A: I look for: Motivation to learn new skills and technologies, a love for supporting and helping people, combined with an active curiosity.

Please refer to this career page for more details.

Ivan Mworozi
Ivan Mworozi
Ivan Mworozi is a Technical Support Engineer at Treasure Data, working on the technical support team that provides enterprise-level assistance to customers around the globe. As the 2018 Gartner Magic Quadrant recognizes, Treasure Data ranks third for overall support in Data Management Solutions for Analytics.