About

Anand Nalya is an experienced Data Engineer with over 17 years of relevant experience in big data application technologies and methodologies. He has a strong interest in pursuing a career in the consumer web space and is currently exploring machine learning, stream processing, and real-time analytics. Anand's specialties include big data applications, performance analysis and optimization, scalability, Kafka, Elasticsearch, Spark, Storm, web application programming, web crawlers, and semantic web. He is currently working as a Data Wrangler at Automattic, where he is responsible for managing and processing large volumes of data. Anand has previously worked as an Analytics Engineer at Cvent, where he contributed significantly to the development of a core framework over Spark in Scala for building data filter/aggregation pipelines. He also developed an annotation-based instrumentation library to capture data from Java services and created Docker/Ansible based deployment pipelines for running standalone Spark jobs. Before joining Automattic, Anand worked as a Module Lead Software Engineer at Impetus, where he was part of the big data team in the research group. He developed a high-throughput data ingestion application using Kafka/HBase and carried out benchmarking for various big data products like QFS, HBase, and Kafka. He also developed core frameworks in Spring for Large Data Analytics Platform and a single-page Webapp framework in jQuery to be used with REST/JSON services. Additionally, he created a high-performance distributed key generator using Zookeeper and a hierarchical and volumetric data sharding algorithm. Anand holds a Bachelor of Engineering degree in Computers from Medi-Caps University. He is proficient in various technologies such as Scala, Java, Ansible, Docker, and Spring. Anand's experience, skills, and passion for big data and web technologies make him a valuable asset to any organization looking to leverage data-driven insights to drive business growth.