Engineering Excellence: An In-Depth Conversation with Swetha Singiri

Swetha Singiri has carved a niche for herself as a seasoned Data Engineering Manager with over 15 years of experience. Her journey from a Project Engineer at Wipro Technologies to leading dynamic teams at top-tier companies like Meta and Intuit showcases her unparalleled expertise in harnessing data to provide strategic insights and influence product strategy. In this exclusive interview, Swetha shares her unique contributions, challenges, and vision for the future of data engineering.

Q1: Swetha, can you share your journey into data engineering and how your background in Finance & Securities has influenced your career?

A: My journey into data engineering began with a foundational role at Wipro Technologies, where I honed my skills in database management and application support. My background in Finance & Securities has been invaluable, particularly in understanding the intricate data needs of financial platforms and ensuring data integrity and security. This experience has allowed me to design robust data architectures and optimize data pipelines, ensuring that strategic insights are accurate and actionable.

Q2: You have led the development of various data platforms and systems. Could you highlight one project that significantly impacted the organization?

A: One project that significantly impacted the organization was leading the overhaul of the video data foundation at a big tech firm. Managing a team of nine, I improved logging coverage and scalability for video content analysis, optimizing data models and reducing CPU usage. This initiative led to faster query times and more efficient data processing. By refining the foundational data model for video consumption and engagement events, we enabled deeper insights and more strategic decision-making, significantly enhancing the firm's overall data capabilities and operational effectiveness.

Q3: What was your role in the Video Ecosystems project at Meta, and how did it contribute to the company's strategic goals?

A: As the manager of the Videos Ecosystem team, my role was to oversee the data engineering and analytics initiatives critical for evaluating and shaping the future of video products at Meta. By developing strategic dashboards and supporting video-wide horizontal efforts, we were able to provide senior leadership with the insights needed to drive product strategy and innovation. This holistic approach connected all aspects of the video ecosystem, from production to monetization, aligning our efforts with the company’s strategic goals.

Q4: Your work often involves cross-functional collaboration. Can you share an example of how this has driven success in your projects?

A: Cross-functional collaboration was key in the Video Quality Machine Learning project. By working closely with product leads and engineering heads, we built a robust data foundation for machine learning algorithms. This collaboration not only improved the quality of video recommendations but also enhanced the user experience significantly. The project's success was a testament to the power of teamwork and the collective expertise of our cross-functional team.

Q5: How did you manage the transformation of Meta's dashboard data quality, and what were the outcomes?

A: Leading a team of 60 data engineers, we embarked on a comprehensive certification process to improve the accuracy, reliability, and visualization consistency of over 200 video dashboards. Through strategic planning and meticulous execution, we achieved a remarkable reduction in data inaccuracies and tripled the number of critical dashboards used for influencing product strategies. This transformation not only elevated the health and quality of our dashboards but also fostered a culture of excellence and continuous improvement.

Q6: Can you discuss the challenges you faced during the migration of legacy pages to the New Pages Experience at Meta?

A: The migration to the New Pages Experience was a complex project that involved coordinating a team of over 40 data engineers. One of the main challenges was ensuring that the migration of approximately 600 data artifacts was seamless and P+ compatible. We overcame this by defining a clear vision, guiding the team with the right technical solutions, and maintaining close collaboration with product leads. The successful migration significantly improved profile watch time and daily active user engagement, contributing to the overall success of the project.

Q7: Your expertise extends to mentoring and professional development. How do you approach this aspect of your role?

A: Mentorship is a core aspect of my leadership philosophy. I prioritize fostering a culture of learning and innovation within my team. By providing regular feedback, conducting training sessions, and encouraging open communication, I empower team members to take ownership of their work and contribute meaningfully. This approach not only helps in professional development but also drives team success and operational excellence.

Q8: You've worked on the txtWeb application at Intuit. What were the key innovations you introduced in this project?

A: The txtWeb application was an exciting project where we developed a recommendations engine to drive user engagement. One of the key innovations was leveraging HDFS for raw data processing with PIG and Sqoop, which significantly improved data analytics and frontend dashboard support. Additionally, we migrated the application's data modeling from MySQL to Netezza and Oracle databases, enhancing the platform’s scalability and performance. These innovations played a crucial role in attracting millions of mobile users and thousands of developers to the platform.

Q9: What role did you play in the overhaul of Meta's creator studio logging and data ecosystem, and what were the results?

A: As the lead data architect and engineer, I spearheaded the comprehensive overhaul of Meta's creator studio logging and data ecosystem. By standardizing logging processes and implementing technologies like the common dimensional framework and user anonymization, we significantly improved data reliability and privacy compliance. The results were remarkable, with a substantial increase in daily active users and significant time and cost savings. This transformation was empowering and significantly improved the overall efficiency of our data management processes.

Q10: Looking ahead, what are your future aspirations and goals in the field of data engineering?

A: Moving forward, I aspire to continue driving innovation in data engineering by leveraging emerging technologies like AI and machine learning. My goal is to lead projects that push the boundaries of data analytics and provide strategic insights that drive business growth. Additionally, I am passionate about mentoring the next generation of data engineers and fostering a culture of continuous learning and excellence. Ultimately, I aim to make a lasting impact on the field by contributing to the development of robust data solutions that address complex business challenges.

Swetha Singiri’s professional journey highlights the profound impact that one individual can have in the realm of data engineering. Her extensive experience and innovative solutions have set new standards for excellence in the industry. Swetha’s dedication to her craft and her continuous quest for knowledge serve as a powerful example for aspiring professionals. Her journey demonstrates that with the right combination of skills, passion, and determination, one can achieve remarkable success and make significant contributions to the technological landscape. As Swetha continues to push the boundaries, her legacy will inspire and guide the next generation of data engineering experts.