Hello, I’m Rani Pinnamaneni, and I’m thrilled to be here today. I’ve spent over five years honing my expertise in data engineering, with a particular focus on building scalable, efficient data pipelines and infrastructure within the AWS ecosystem.
Let me share a bit about my journey. Currently, I’m working as a Principal Data Engineer at Ascentt Systems Inc., where I lead a team that designs and implements end-to-end data solutions. One of the most significant projects I’ve led involved working with data from multiple sources, including complex JSON and image data, which we needed to unnest, flatten, and transform for ingestion into AWS S3 and OpenSearch. We used AWS Glue for ETL processes and AWS Batch for handling large volumes of image data. This project was not just about processing data efficiently—it was about ensuring that our solutions could scale seamlessly as the volume of data increased. This experience has given me a deep understanding of how to optimize data pipelines, making them faster and more reliable, which is exactly the kind of challenge I thrive on.
Before Ascentt, I had the opportunity to work at Toyota Motors North America, where I focused on optimizing SQL queries and improving data workflows. My work there resulted in significant performance improvements across their data systems. I take pride in my ability to dive deep into data architectures, identify bottlenecks, and implement solutions that are both innovative and cost-effective. My brief tenure at Centene Corporation further strengthened my skills in data management, where I developed robust, scalable data solutions that were aligned with the company’s strategic goals.
What drives me is the intersection of technology and business. I hold a Master’s degree in Business Analytics, which has equipped me with the ability to see beyond just the technical aspects of data engineering. I understand how critical it is for data solutions to not only function efficiently but also to contribute to achieving broader business objectives.
I’m particularly excited about the opportunity at Meta because it represents the forefront of data engineering and innovation. The chance to contribute to large-scale projects, where my experience with AWS, PySpark, SQL optimization, and data architecture can make a real impact, is something I’m genuinely passionate about. I’m eager to bring my skills to Meta and help push the boundaries of what’s possible in data processing and analysis, ensuring that we’re not just keeping up with the pace of data but leading the way in how it’s utilized.
Thank you for considering my application. I look forward to the possibility of contributing to Meta's mission and continuing to grow as a data engineer in such a dynamic environment."**
