I specialize in architecting and implementing robust data solutions in complex and high-volume environments. Leveraging tools like PySpark for ETL, Apache Airflow for pipeline orchestration, and Apache Kafka for real-time data processing, I design and execute end-to-end data workflows. With expertise in Azure Data Platform services and machine learning techniques, I optimize data processes for efficiency and scalability. My proficiency spans from data modeling and ETL development to BI… Show more I specialize in architecting and implementing robust data solutions in complex and high-volume environments. Leveraging tools like PySpark for ETL, Apache Airflow for pipeline orchestration, and Apache Kafka for real-time data processing, I design and execute end-to-end data workflows. With expertise in Azure Data Platform services and machine learning techniques, I optimize data processes for efficiency and scalability. My proficiency spans from data modeling and ETL development to BI solutions and ad-hoc analysis, ensuring actionable insights for stakeholders. Passionate about driving impactful data-driven decisions, I excel in collaborating with cross-functional teams to deliver innovative solutions while adhering to project guidelines and SLAs. Show less

I specialize in building and optimizing data solutions within diverse environments, leveraging a blend of cutting-edge technologies. With expertise in Spark Streaming, Apache NiFi, and AWS services, I architect end-to-end data pipelines for near-real-time data processing and storage in Hadoop Distributed File System (HDFS). My role involves designing data models, orchestrating EMR clusters on AWS, and implementing complex Python and Scala code for data analytics and application requirements. I… Show more I specialize in building and optimizing data solutions within diverse environments, leveraging a blend of cutting-edge technologies. With expertise in Spark Streaming, Apache NiFi, and AWS services, I architect end-to-end data pipelines for near-real-time data processing and storage in Hadoop Distributed File System (HDFS). My role involves designing data models, orchestrating EMR clusters on AWS, and implementing complex Python and Scala code for data analytics and application requirements. I thrive in optimizing data performance through Spark, Hadoop, and Kafka, driving significant increases in user engagement and conversions. Proficient in DevOps practices, I deploy and manage solutions using Docker, AWS Lambda, Glue, and Terraform, ensuring high availability and scalability. Passionate about exploring new technologies, I continuously innovate to deliver impactful data-driven solutions. Show less

I specialize in architecting and constructing multi-terabyte, end-to-end Data Warehouse infrastructure on Confidential Redshift, facilitating seamless handling of millions of records daily. Leveraging tools like SSRS and SSIS, I design and deploy data pipelines to extract, transform, and load data from diverse sources. My expertise extends to developing and optimizing ETL processes using technologies such as Kafka, Hive SQL, Presto SQL, and Spark SQL. With a strong grasp of AWS services like… Show more I specialize in architecting and constructing multi-terabyte, end-to-end Data Warehouse infrastructure on Confidential Redshift, facilitating seamless handling of millions of records daily. Leveraging tools like SSRS and SSIS, I design and deploy data pipelines to extract, transform, and load data from diverse sources. My expertise extends to developing and optimizing ETL processes using technologies such as Kafka, Hive SQL, Presto SQL, and Spark SQL. With a strong grasp of AWS services like EC2, S3, EMR, and DynamoDB, I ensure high availability and scalability while managing security groups and implementing continuous integration and deployment practices. Proficient in data modeling using ERwin, I design logical and physical models, define facts and dimensions, and create data marts following Ralph Kimball's methodology. I excel in performance optimization, employing techniques such as workload management in Redshift and tuning environments for enhanced query performance. Collaborating closely with stakeholders, I deliver impactful data solutions and meticulously document specifications and requirements. Show less

I specialize in managing and optimizing large-scale data environments, with a focus on Hadoop ecosystem technologies. Leveraging tools like HBase and Sqoop, I design and implement data pipelines for efficient loading and processing of structured data. My expertise extends to utilizing AWS Glue for data transformation and cleansing, as well as developing custom components like Hive UDFs to enhance analytics capabilities. With a deep understanding of file formats and cluster coordination services… Show more I specialize in managing and optimizing large-scale data environments, with a focus on Hadoop ecosystem technologies. Leveraging tools like HBase and Sqoop, I design and implement data pipelines for efficient loading and processing of structured data. My expertise extends to utilizing AWS Glue for data transformation and cleansing, as well as developing custom components like Hive UDFs to enhance analytics capabilities. With a deep understanding of file formats and cluster coordination services like Zookeeper, I ensure robust data management and analysis. Proficient in MapReduce, Pig, and Hive, I extract valuable insights from data and streamline processes for downstream systems. Additionally, I excel in technical documentation, facilitating smooth operations and knowledge sharing within the team. Show less

In my current project, I specialize in leveraging Hadoop ecosystem technologies to handle and analyze large volumes of data efficiently. I utilize Sqoop for seamless data ingestion from MySQL servers into Hadoop clusters, and PySpark/Spark SQL for robust data cleansing and transformation tasks. My role involves creating Hive tables, optimizing Pig queries, and developing Hive queries to process and analyze data stored in HDFS. Additionally, I integrate real-time unstructured data using Apache… Show more In my current project, I specialize in leveraging Hadoop ecosystem technologies to handle and analyze large volumes of data efficiently. I utilize Sqoop for seamless data ingestion from MySQL servers into Hadoop clusters, and PySpark/Spark SQL for robust data cleansing and transformation tasks. My role involves creating Hive tables, optimizing Pig queries, and developing Hive queries to process and analyze data stored in HDFS. Additionally, I integrate real-time unstructured data using Apache Flume, and employ MapReduce for processing both structured and unstructured data sets. With a focus on ETL tasks, I design solutions for data acquisition, transformation, cleaning, and storage on HDFS. Leveraging Scala and Spark Streaming, I develop Spark code for faster testing and processing, while applying machine learning algorithms from Spark MLib to analyze data and enhance accuracy. Finally, I visualize data outcomes using Tableau, providing actionable insights from machine learning models. Show less