Rakesh D.

✨ Seasoned software professional with 20+ years of experience in end-to-end software development, including 8+ years specializing in Big Data technologies and cloud-based solutions. Proven expertise in building scalable, high-performance data platforms using Apache Spark, Hadoop, Hive, Cassandra, and programming in Scala, Python, Java and C++. ✨ I focus on designing robust, enterprise-grade Big Data and Data Engineering architectures on GCP, AWS, and Azure, both in on-prem and cloud environments. My role involves solution architecture, technical leadership, and hands-on development of critical components. ✨ I am passionate about leveraging my experience to build cutting-edge data and AI solutions. Open to senior technical roles, consulting opportunities, and innovative startup environments. 🔹 Keen eye on scalability, sustainability of the solution 🔹 Can come up with maintainable & good object-oriented designs quickly 🔹 Highly experienced in seamlessly working with remote teams effectively 🔹 Aptitude for recognizing business requirements and solving the root cause of the problem 🔹 Can quickly learn new technologies 🔹 Transparency, Dedication, Qualtity and Satisfaction Guaranteed Sound experience in following technology stacks: ✨ Big Data: Apache Spark, Spark Streaming, HDFS, Hadoop MR, Hive, Apache Kafka, Cassandra, Google Cloud Platform (Dataproc, Cloud storage, Cloud Function, Datastore/Firestore, Pub/Sub), Cloudera Hadoop 5.x ✨ Languages: Scala, Python, Java, C++, C, Scala with Akka and Play frameworks ✨ Build Tools: Sbt, Maven ✨ Databases: Postgres, Oracle, MongoDB/CosmosDB ✨ GCP Services: GCS, DataProc, Cloud functions, Pub/Sub, Data-store, BigQuery ✨ AWS Services: S3, VM, VM Auto-scaling Group, EMR, S3 Java APIs, Redshift, MongoDB ✨ Azure Services: Blob, VM, VM scale-set, Blob Java APIs, Synapse, CosmosDB ✨ Other Tools/Technologies: Kubernetes, Dockerization, Terraform Worked with different types of Input & Storage formats: CSV, XML, JSON file, Mongodb, Parquet, ORC