Robin Sutara, field CTO, Databricks
Describe your career to date
After starting my career repairing electrical and weapons systems on Apache helicopters, I made the foray into computers by doing hardware repair for several years while obtaining my MCSE certification via night school.
With this education, I was able to start a career that spanned more than two decades at Microsoft in various technical, operational, and leadership roles. From technical consulting to data analyst to chief operating officer of Azure Data Engineering, I culminated my career there as the CDO of Microsoft UK.
During this time, I also pursued educational opportunities to grow, such as a juris doctorate, Master of Law in Intellectual Property, and a graduate certification in engineering leadership. In each of these experiences, I learned best practices for leading and implementing a data-led organisation through people, process, and technology. And now with Databricks, I have the amazing opportunity to share that journey and those learnings with others on similar paths to help them become data-centric organisations more quickly.
What key skills or attributes do you consider have contributed to your success in this role?
I have found the skills of collaboration, negotiation, storytelling, and troubleshooting to be invaluable in my journey. In data, we are often asked to tie business and technology together in new ways; to bring disparate teams together to drive toward tangible solutions, leveraging data, unlocks amazing opportunity and innovation.
What level of data maturity do you typically encounter across your client base and what tends to hold this back?
I have had the opportunity to work with hundreds of organisations around the world, representing the full spectrum of data maturity. For those that are still relatively novice in their data journey, there is primarily a focus on basic business insights and reporting. As organisations begin to mature, we see a shift from backward looking to forward. They begin to leverage their data to be more predictive and preventative - leveraging advanced data science, AI, and machine learning.
Where I see organisations struggle is when they depend on technology to solve gaps in people and process. Successful data transformation requires strong change management that is inclusive of people, process and technology. Only by ensuring that you have a great foundation with the technology - and investing in the cultural aspects of your organisation - can you mature in your data journey.
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