Rakshit Makadiya
Apps Dev Programmer Analyst - Big Data | Big Data Enthusiasts | Hadoop | Sqoop | Hive | Spark | Scala | Kafka | SQL | Python | AWS (EMR,Glue,Redshift,Athena) | Talend | Autosys
- Role
- Officer - Apps Dev Programmer Anlayst - Big Data at Citi
- Location
- Pune, MH, IN
- LinkedIn followers
- 500 followers
About Rakshit Makadiya
Having around 5+ years of IT experience and Big Data Developer with around 3.5 years of experience in Big Data development and data analytics, an expert in Apache Spark and Hadoop ecosystem technologies.My work includes data ingestion and transformation across various platforms, utilizing Hadoop, Spark, SQL, and AWS technologies. Key achievements include successfully ingesting and transforming data for analytics in Big Data Projects, optimizing processes for greater efficiency, and managing data aggregation projects for retail clients. I am passionate about leveraging data solutions to help organizations gain insights and improve decision-making processes.Good knowledge on Big Data - HDFS | Map Reduce | Sqoop | Hive | Spark | Spark Streaming | Scala | Kafka | AWS EMR | SQL | Python.Experience in Data visualization tools :1. Mode Analytics2. LookerETL tools : Talend & Databridge.Experienced in working on data from multiple domains and converting it into meaningful insights.
Experience
Officer - Apps Dev Programmer Anlayst - Big Data
Aug 2023 — Present · Maharashtra, IN
As part of the team we were consuming feeds as per requirements and delivering it to our downstream teams.• Involved in Raw Data processing (structured and unstructured data) – Stream Ingestion• Mostly responsible for file-based, DB-based, and API-based ingestion through Talend and Data Bridge. • Developed and writing a shell script for optimization of jobs for deployment purposes. • Developed and optimized distributed data processing pipelines in transforming data through Pyspark/Scala for optimization.• Implemented ETL workflows using Pyspark to extract, transform and load from diverse sources (HDFS, S3, relational Databases).• Tuned Pyspark jobs by optimizing transformations, actions and partitioning to improve runtime performance.• Automated data workflows by integrating Pyspark scripts into Autosys/ Apache Airflow for scheduled and event-driven processing.
Education
The Poona Gujrati Kelwani Mandals H.V.Desai Senior College of Arts, Science & Commerce ,Budhawar Peth,Pune 2
Master of Science-comp
2015 — 2019
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