Mohammad Sameer Email & Phone Number

Irving, TX, US

Weehawken, New Jersey, United States

• Extensively collaborated with the Azure cloud platform, showcasing proficiency in HDInsight, Data Lake, Databricks, Blob Storage, Data Factory, Synapse, SQL, SQL DB, DWH, and Data Storage Explorer.
• Executed data ingestion into multiple Azure Services, including Azure Data Lake, Azure Storage, Azure SQL, and Azure DW, followed by processing the data within Azure Databricks.
• Demonstrated expertise in designing and configuring Azure Cloud relational servers and databases, aligning with current and future business requirements.
• Implemented medallion architecture for the event and batch data leveraging databricks Lakehouse and unity catalog for data governance.
• Implemented DABs as part of implementing framework for deploying jobs and integrate with Githubworkflow actions.
• Configured Input & Output bindings of Azure Function with Azure Cosmos DB collection for seamless data read and write operations.

Missouri, United States

• Engaged in the design and deployment of multi-tier applications, leveraging a comprehensive suite of AWS services such as EC2, Route53, S3, RDS, Dynamo DB, SNS, SQS, and IAM. Focused on ensuring high availability.
• Crafted AWS Data pipelines, utilizing AWS API Gateway to receive responses from AWS Lambda, extracting and transforming data into JSON format, and storing it in AWS Redshift.
• Developed scalable AWS Lambda code in Python, specifically designed for handling nested JSON files, encompassing tasks such as conversion, comparison, and sorting.
• Implemented Spark Applications using Scala, executing an Apache Spark data processing project to manage data sourced from various RDBMS and Streaming platforms.
• Enhanced the performance and efficiency of existing Spark jobs, transitioning from MapReduce scripts to Spark SQL.
• Proficiently collected real-time data from an AWS S3 bucket using Spark Streaming, executed necessary transformations and aggregations, and persisted the data in HDFS.

Oak Brook, Illinois, United States

• Employed Azure Data Facto ry, T-SQL, Spark SQL, and U-SQL in Azure Data Lake Analytics to extract, transform, and load data from various source systems into Azure Data Storage services. This included data ingestion.
• Successfully implemented proof of concepts for both SOAP and REST APIs and harnessed REST APIs to retrieve analytical data from diverse data feeds.
• Developed pipelines within Azure Data Factory (ADF) using Linked Services, Datasets, and Pipelines to extract, transform, and load data from sources such as Azure SQL, Blob storage, Azure SQL Data Warehouse, write-back.
• Showcased proficiency in developing SQL scripts for automation purposes, streamlining data processes.
• Utilized PY-Spark and Spark-SQL to build Spark applications for data extraction, transformation, and aggregation from various file formats, enabling comprehensive analysis and insight discovery.
• Took responsibility for estimating cluster sizes and meticulously monitored and troubleshot the Spark Databricks cluster for optimal performance.

India

• Extracted diverse datasets, encompassing customer behavior, sales and revenue data, as well as supply chain and logistics data, from HDFS.
• Utilized Apache Nifi, an open-source data integration tool, to efficiently transfer data to AWS S3, ensuring powerful and scalable dataflows.
• Implemented Python scripts for data validation and cleansing before storing the refined data in S3.
• Employed PySpark, a distributed computing framework with a Python API, to process and transform the data.
• Loaded the transformed data into AWS RedShift data warehousing for comprehensive data analysis.
• Scheduled the entire pipeline using Apache Oozie, a workflow scheduler system designed to manage Apache Hadoop jobs.

India

• Participated in the assessment of both functional and non-functional requirements for data processing tasks.
• Installed and configured Hadoop MapReduce HDFS, developing multiple Java-based MapReduce jobs for data cleaning and pre-processing.
• Configured and utilized Pig, writing Pig Latin scripts, and also integrating Pig Latin into MapReduce jobs.
• Managed and reviewed Hadoop log files to ensure system integrity and performance.
• Imported data from MySQL to HDFS using Sqoop on a regular basis, establishing efficient data transfer processes.
• Developed scripts and batch jobs for scheduling various Hadoop programs, optimizing workflow management.