Manish Agarwal is Vice President of Data and Analytics at Skechers, where he leads enterprise data, analytics, and AI initiatives to drive scale, speed, and business impact.
He brings more than 25 years of experience building and scaling data and analytics functions, progressing from hands-on engineering roles to leading enterprise-wide transformations. Early in his career, Manish architected one of the first internal Database-as-a-Service platforms, well before cloud computing became mainstream. He later led the development of a petabyte-scale data platform processing more than 7 billion records daily, applying machine learning to segmentation, targeting, and predictive analytics.
Manish’s career spans Fortune 500 companies and high-growth environments, including Nortel, Deloitte, Myspace, Oracle, MGM Resorts, Hertz, and Skechers. These experiences shaped him as a pragmatic innovator, comfortable designing structured, scalable platforms while moving quickly when business demands require agility. His work has included building knowledge engines, deploying robotics, and delivering AI-powered recommendation, forecasting, and optimization systems across industries.
More recently, Manish has expanded traditional AI and machine learning capabilities with generative AI, developing intelligent solutions that bridge human intuition and machine-scale reasoning. This includes launching a generative AI-powered conversational business intelligence platform that delivers contextual, real-time decision support.
Known for tackling complex challenges others considered impossible, Manish has led initiatives such as migrating a 1.7-petabyte data warehouse with zero downtime and deploying AI-driven robotics that reduced delivery times by 75%. He remains hands-on, focused on making data and AI practical, trusted, and transformative.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“Effective data and AI leadership demands a clear balance between innovation and practicality. The most critical traits are strategic patience, curiosity, trust-building, business acumen, and the ability to translate complexity into clarity.
“I’ve found that starting small with well-defined, bite-sized initiatives is often the best way to earn confidence and demonstrate value. Chasing the latest tech trend without alignment to business needs risks credibility. Instead, I focus on understanding where the business is headed, identifying the right opportunities for AI or automation, and then proving value quickly through pilots and iterative delivery.
“Trust is a long game. For business stakeholders to embrace data and AI, they need leaders who listen, communicate clearly, and bring them along on the journey. Being transparent, outcome-focused, and responsive has helped me embed analytics across functions.
“In my organization, the most influential skills have been the ability to frame problems in business terms, speak the language of the C-suite, and use technology as a means to an end, not the end itself. Combining technical insight with commercial thinking and a willingness to experiment has helped me unlock value while building momentum for change.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“Cultivate self-awareness and executive presence before technical excellence.
“Aspiring data and AI leaders often focus on mastering technology, but the real differentiator at the executive level is emotional intelligence. Self-awareness is the ability to know how you’re perceived, how you influence others, and how you show up in strategic conversations. It can unlock more trust and impact than any algorithm.
“You cannot lead through complexity without connecting with people. Learn to read the room, adjust your tone, and communicate a vision that resonates with both technical teams and business stakeholders. Build credibility by listening more than speaking, aligning data efforts with business priorities, and staying focused on outcomes that drive real value.
“Data and AI are tools. Influence, clarity, and empathy are the enablers. If you’re aiming for the C-suite, lead with purpose, not just precision.”