Ramachandra Nalam is an experienced data professional with over five years of expertise in designing, developing, and managing robust data pipelines, software systems, and cloud-based solutions. He specializes in leveraging modern data technologies such as SQL and Tableau, along with programming languages including Python, to build scalable and efficient data solutions. He is AWS Certified in Data Analytics – Specialty and Tableau Desktop certified.
Currently serving as a Data Engineer at Snap Inc. in Bellevue, Washington (since January 2026), Ramachandra works on large-scale data infrastructure and streaming systems that support high-volume platform analytics and machine learning workflows.
Previously, as a Data Engineer at Meta in Seattle (September 2024 – December 2025), Ramachandra optimized SQL processes that reduced cluster CPU utilization by 34%, significantly decreasing operational overhead and on-call time. He developed high-throughput streaming pipelines processing over one million events per second and built centralized dashboards to monitor machine learning model performance for Facebook Messenger and Instagram Direct.
Earlier, as a Software Engineer at Amazon (October 2022 – September 2024), he led the optimization and support of ETL pipelines within AWS using services such as AWS Glue and Aurora DB. He developed large-scale streaming pipelines using Apache Kafka, processing over 500,000 events per second, reduced latency by 35%, and maintained Spark applications handling more than 1 TB of data daily. His work optimizing Redshift queries reduced CPU utilization by 52%, substantially lowering weekly on-call time. He also implemented workflow automation using Apache Airflow and mentored cross-functional teammates on data visualization tools.
At the University at Buffalo (January 2022 – August 2022), Ramachandra utilized Snowflake to analyze 20,000 student records and implemented machine learning models, achieving 88.74% accuracy with a Random Forest model. His work contributed to a strategic initiative that improved the university’s four-year graduation rate for identified at-risk students.
Earlier in his career as a Freelance Data Engineer in India (August 2018 – August 2020), he designed end-to-end ETL processes handling millions of records, developed PySpark jobs for large datasets, implemented a data lake architecture capable of processing over 10 TB of data, and built Python-based security analytics solutions that reduced risks by 75%.
Ramachandra holds a Master of Science in Data Science from the University at Buffalo (GPA: 3.3/4.0) and a Bachelor of Technology in Computer Science from KL University, India (GPA: 3.35/4.0). His technical expertise spans programming languages such as Java, Python, R, Scala, SQL, and JavaScript; databases including MySQL, Oracle, and PostgreSQL; and a wide range of AWS cloud services.