How to Make Your Mark as a Woman in Big Data

by   |   December 28, 2016 5:30 am   |   1 Comments

Kavitha Mariappan, VP of Marketing, Databricks

Kavitha Mariappan, VP of Marketing, Databricks

As a marketing executive at big data startup, my day often revolves around analyzing and discovering hidden trends and patterns from our lead data, and providing guidance to my team on strategies to maximize our conversion rates.

Marketers leverage big data in a number of ways ranging from customer segmentation, customer insights, and predictive lead scoring, to personalized marketing and sentiment analysis. Some marketing teams rely heavily on big data for off-the-shelf marketing technology solutions to enable programmatic marketing, content optimization, predictive response targeting, attribution tools, performance analytics and more. While others are evaluating open source software to build capabilities that will help them to quickly and correctly act on their own data. Either way, data analytics has certainly become a top of mind for CMOs in 2016.

The marketing tech landscape is becoming more complex and diverse. As the need for more predictive and deterministic data in marketing decision making increases, so do new leadership roles needed to acquire and manage these, invariably integrating the technology and marketing worlds. As an engineer turned tech marketer, this new paradigm presents a perfect storm that helps me combine my engineering and marketing skills to do what I love the most – solve complex problems.

Despite this shift in big data technology innovation that is driving tremendous growth and opportunities, women still play a small role in this arena. Gender disparity in tech companies is nothing new and has existed for decades. Although concerted efforts are being made by companies and women’s awareness groups to narrow this gap, the statistics over the past five years indicate that we still have much work to do. Ironically these numbers aren’t too different from when I entered my undergrad engineering program in the early 90s, or when I first entered the workforce twenty years ago.

Another vector to this tech gender gap issue is how far its reach can potentially extend to. As more and more domains become technology-centric – i.e. marketing as a function now requires candidates to have more in depth technical and analytical skills set – the ability to combine deep technical knowledge as a subject matter expert, with data analytics, digital and growth marketing skills, to the traditional marketing toolkit becomes increasingly necessary. As such, traditionally female-dominated roles within tech companies such as marketing will also likely be impacted by this phenomenon. I encounter this every day, as do other CMOs, in finding qualified candidates, hiring and building the technology marketing teams for tomorrow.

There are several reasons why women are underrepresented in tech, especially big data. First, the lack of female role models in tech and in the C-Suite makes it less attractive for women to pursue careers in this area. Second, the lack of support networks along the path to help, guide and motivate women at every stage in their tech careers. Third, retention of women technologists within the workforce is a major problem due to cultural and work-life integration issues i.e. the leaky pipeline issue indicating a 50% decline in representation of women from entry to executive levels. Fourth, tech culture in general needs to shift from the typical “dude-dominated” persona of today to one that is more encompassing of a rich and diverse workforce.

Despite all, making your mark as women in big data is not only possible but a direction I personally hope many women will continue to pursue. Drawing from my personal experience, I have always felt that there are opportunities in what we may consider to be adversity. Yes, you may still be the minority in your CS class, or in your first team meeting at work, but my advice to women in big data is to embrace that, seek out opportunities and make them yours.

At Databricks, we strive to ensure that women are well-represented across the different functions within the company, and we aggressively work to recruit talented women. Our goal is to build a work environment where everyone feels welcome, and can do their absolute best work. That value is shared by every member of our executive team, and our investors as well.

I am confident that this tech gender diversity gap will continue to narrow in the coming years and this opinion is only validated as I watch my 13 year old daughter learn to code on her own, and draw strength from her online network of female programmers. Some parting thoughts for women considering a career in big data:

  1. Stretch your technical skills: Big data is both competitive and highly cerebral. Invest in your learning and build that toolkit. Ask the stupid questions – it is only going to help you sharpen that saw. Get your hands dirty and explore the technologies and tools out there. Make open source your sandbox for learning.
  2. Seek out mentors and find networks: Find thought leaders and experts in your area of interest – these can be both women and men. Reach out to them and build that network. You will be surprised by how many experts out there are willing to be in your corner – after all, they have all had to start somewhere themselves.
  3. Embrace your inner ‘girl’: The one thing I learned early on in my career in tech is that you are better off to be yourself. Don’t try too hard to fit in with the guys just to feel accepted. Focus on who you are and harness your individuality and talent. It will be less tiresome, and you’ll find that both women and men will appreciate you more for it.
  4. Take your seat at the table: The only way you are going to win is to play. Make your ideas and opinions heard because they matter. Diversity of opinion and input enriches the final outcome of any project. Learn to debate pragmatically and not emotionally – you can’t win every professional debate but you will come away with a better outcome with every professional discourse, and believe it or not, it will enrich you as a person.
  5. Stay hungry: You have to want to be in this for the long haul. Set defined goals, make a plan to get there and put in the work. As Margaret Thatcher once said, “plan your work for today and every day, then work your plan.”

 

Kavitha Mariappan is the Vice President of Marketing at Databricks. Kavitha heads up Databricks’ end-to-end global marketing efforts. She brings more than 20 years of extensive industry experience in product and outbound marketing, product management, and business development to Databricks. Prior to Databricks, Kavitha was the VP of Marketing at Maginatics (acquired by EMC), where she built and led the team responsible for all aspects of marketing and communications. Her previous professional experience includes leadership roles at Riverbed Technology and Cisco Systems, Inc. Kavitha has a Bachelor of Engineering in Communication Engineering from the Royal Melbourne Institute of Technology, Australia.

 

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One Comment

  1. Hilary Jones
    Posted December 28, 2016 at 6:55 pm | Permalink

    Thank you for the excellent post! I am just starting my analytics career at age 51, and your advice will be very useful.

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