WiBD Berlin Chapter Interview with Meyyar Palaniappan

When data becomes the new currency and algorithms shape business decisions, representation matters more than ever. Yet women make up just 28% of the global tech workforce—a statistic that Meyyar Palaniappan is actively working to change. As a cloud expert, speaker, founder, and Director of Women in Big Data Munich, she’s building bridges between technical excellence and inclusive leadership. Her journey from a machine learning master’s student at Technical University of Munich to building and leading communities reveals how the passion for data can fuel both career success and systemic change.

As AI and cloud technologies reshape business operations, Meyyar Palaniappan stands at the intersection of technical innovation and community building. Through her work with the AWS Women’s User Group Munich and Women in Big Data Munich, she’s not just tracking engagement metrics—she’s creating ripple effects of empowerment that transform careers and challenge industry norms.

The Technical Journey: From Student to Leader

You wear many hats: cloud expert, speaker, founder, director. Can you tell us about your journey and how you first became passionate about data and cloud technologies? What does ‘data-driven leadership’ mean to you in practice, and how do you apply it in your day-to-day decision-making?

I fell in love with Machine Learning (ML) at my master’s at Technical University of Munich (TUM). My master thesis at TUM was in ML as well – credits goes to Andrew Ng’s course on ML, and to my university lecturers at that time – Thomas Stibor (he is the chair of IT security at TUM, currently) and my thesis supervisor – Han Xiao (he is the CEO at Jina AI). At the end of my Masters, I secured an internship at Microsoft Bing, followed by my full-time software engineering role at Amazon Search Platform – all revolving around ML.

Data was baked-in all along the way, and I like the chaos around it. I rejoice the moments when I can make sense out of this chaos! It is quite addictive, when you can connect the dots.

Data-driven leadership is all about working backwards from the data not just at hand, but across relevant domains and sectors. With the new EU Data Act, this challenge of connecting the dots will only get more interesting!

Some concrete examples on how I use data in my communities: In my role as Director of Women in Big Data Munich, I use data to track community engagement metrics, measure the impact of our events, and identify gaps in representation to guide our goals and decisions.

When making decisions about AWS Women’s User Group Munich initiatives, I analyse attendance patterns, feedback scores, and participant surveys to determine which topics resonate most and adjust my strategy accordingly.

Building Inclusive Communities in Tech

As the Director of Women in Big Data Munich and founder of the AWS Women’s User Group, what do you see as the biggest challenges and opportunities for women entering the tech/data space today?

Challenges:

• Persistent representation gaps: Women still represent only 28% of the global tech workforce, with significant attrition at mid-career levels (56% leave tech mid-career)

• Bias and workplace culture: Gender bias, limited mentorship opportunities, and workplace culture issues continue to create barriers

• Pay inequality: Despite progress, wage gaps persist across technical roles

• Lack of role models: Limited visibility of women in senior technical and leadership positions

• Fluctuating flexible work options: With Corona, remote working option increased, but then in the last few quarters this is also reversing, affecting caregivers (especially women in the work force).

Opportunities:

• Growing recognition: 94% of data and AI leaders now recognize that AI interest is driving greater focus on data, creating more opportunities in our field

• Skill demand: The rapid evolution of cloud and AI technologies means there’s high demand for expertise, creating entry points for career changers

• Community Building: Networking is important than ever and opens new opportunities, when policies and programs at the employer are constantly evolving.

What has been the most rewarding part of building and leading these communities?

The most rewarding aspect has been witnessing the ripple effect of empowerment. When I see a woman who joined our community as a beginner later become a speaker at our events, or when someone lands their dream job after building confidence through our workshops, it validates everything we’re doing.

What’s particularly fulfilling is seeing how our communities become launching pads for others to create their own initiatives. Members don’t just consume content – they become contributors, mentors, and leaders themselves. We’ve created an ecosystem where knowledge sharing flows in all directions.

The personal connections are equally meaningful. Building a space where women can discuss technical challenges without judgment, share career advice, and celebrate each other’s achievements has created lasting professional relationships that extend far beyond our formal events.

How do you balance technical advancement with creating inclusive spaces for women and underrepresented groups in tech?

Balance is a blurry line. To the audience, it looks like I am juggling all the balls all the time. But no, I do skip some in-between, let them fall or hand them over to my family/team, to juggle for a while (keyword – delegation). It is not easy, but manageable with planning and experimentation.

I pick two to three top priorities for a day to achieve and try to get to them by the end of the day. And each day, these are different things, helping to keep a balance across the board. And having deadlines immensely helps 😉

The Future of Cloud and AI Leadership

Cloud technology is evolving rapidly — what current trends excite you most, and what should leaders be paying attention to?

Several trends are particularly exciting right now:

AI-Cloud Integration: The integration of AI into cloud services is revolutionizing business operations. We’re seeing AI-powered optimization becoming standard, with cloud providers heavily investing in GenAI capabilities that are transforming how we approach data processing and analysis.

Edge-to-Cloud Convergence: The seamless integration between edge computing and cloud services is creating new possibilities for real-time data processing and decision-making, especially important for IoT and autonomous systems.

Quantum Cloud Services: We’re at the early stages of quantum computing becoming accessible through cloud platforms, which will eventually transform computational approaches to complex data problems.

Governance and Sustainability: There’s increased focus on complex governance, cost optimization, and environmental considerations in cloud adoption – areas where data-driven decision making is crucial.

As leaders, we should pay attention to the skills gap this creates. The rapid evolution means continuous learning isn’t optional – it’s essential for staying relevant.

How do you think AI and big data are changing leadership and the future of work?

AI and big data are fundamentally reshaping leadership in three key ways:

Decision-Making Speed and Accuracy: We can now make informed decisions faster with real-time data insights and predictive analytics. This shifts leadership from intuition-based to evidence-based decision making.

Democratization of Insights: AI tools are making complex data analysis accessible to non-technical leaders, breaking down silos between technical and business teams. This means every leader needs to become somewhat data-literate.

Workforce Transformation: We’re seeing the emergence of human-AI collaboration rather than replacement. Leaders need to orchestrate hybrid teams where AI handles routine analysis while humans focus on strategic interpretation and creative problem-solving.

The future of work will require leaders who can balance technical understanding with human empathy – managing AI systems while leading people through the anxiety and excitement of technological change. This is why inclusive leadership in tech is more critical than ever.

Mentorship and Advice for the Next Generation

Was there a mentor or a defining moment that shaped your career or leadership style?

Not just one, but many! If I must pick two names, it would be Constantin Gonzalez and Jeff Caselden! My mentorship meetings with Jeff (my skip level manager and then was General Manager, AWS, Dublin) were particularly valuable because they focused on strategic thinking and leadership. Jeff had a unique ability to ask probing questions that forced me to examine my assumptions and think several steps ahead, which proved invaluable as I navigated increasingly complex projects and stakeholder relationships.

Constantin, a Principal Solutions Architect based in AWS Munich, brought a valuable technical leadership perspective to our mentorship relationship. His technical depth and customer-facing experience provided insights that complemented Jeff’s strategic guidance. We discussed and brainstormed concrete technical solutions, and complex architectural concepts.

What made both mentorship relationships particularly effective was their structured yet flexible nature. We established regular meeting cadences that allowed for consistent development while remaining adaptable to urgent issues or opportunities that arose. Both mentors encouraged me to bring real challenges I was facing, rather than abstract scenarios, which meant our discussions had immediate practical application.

What advice would you give to young women or career-changers who want to transition into the data or cloud field but feel intimidated by the technical barrier?

My advice centres on three key principles:

Start with Curiosity, Not Perfection: you don’t need to master everything before starting. I fell in love with this field through Andrew Ng’s course – begin with fundamentals and let your curiosity guide you deeper. The technical barrier feels intimidating, but it’s just a series of learnable steps.

Leverage Community: join groups like Women in Big Data, AWS user groups, or online communities. The learning curve is steep, but you don’t have to climb it alone. Find mentors, ask questions, and don’t be afraid to admit what you don’t know – that’s how we all started.

Focus on Problem-Solving: remember that technology is a tool to solve real problems. Start by identifying problems you’re passionate about solving, then learn the technical skills needed to address them. This approach makes the learning more meaningful and sustainable.

Most importantly, imposter syndrome is real but not insurmountable. Every expert was once a beginner. And every expert is a beginner in another ‘new’ field. The field needs diverse perspectives and fresh approaches – your unique background and viewpoint are assets, not disadvantages – so never undersell yourself!