Nihal Mohammed Email & Phone Number

Charlotte, Nc, Us

Chicago, Illinois, United States

• Successfully migrated financial datasets from Workday to AWS, ensuring data integrity and accuracy throughout the process. Leveraged AWS S3 for scalable and secure storage of financial data, ensuring high availability and durability.• Used AWS Glue to create and manage ETL pipelines, automating the extraction, transformation, and loading of data into AWS data stores.• Implemented AWS Redshift for efficient data warehousing solutions, enabling fast query performance and data analytics.• Implemented logging systems adhering to industry standards and compliance requirements, ensuring robust monitoring and auditing capabilities.• Secured system authentication using SAML and MFA, enhancing the security posture and reducing the risk of unauthorized access.• Deployed storage solutions with advanced protection mechanisms to prevent unauthorized modifications, ensuring data integrity and confidentiality.• Integrated security code review processes within the CI/CD pipeline to identify and remediate vulnerabilities early in the development cycle.• Ensured precise system time synchronization using NTP, crucial for maintaining accurate timestamps in logs and other security-related activities.• Developed data processing and analysis scripts using PySpark, handling large-scale data efficiently.• Aligned systems and configurations with established security baselines, ensuring consistent and standardized security measures across the infrastructure.• Analyzed security reports, identified potential threats, and implemented remediation measures to mitigate identified risks.• Utilized NiFi for building robust ETL pipelines, enabling seamless data flow and transformation across various data sources.• Leveraged security tools like SPLUNK and Chronicle for comprehensive monitoring, analysis, and incident response.

Chicago, Illinois, United States

•Drove the migration of legacy ETL jobs to Spark, optimizing them for cloud-based execution and preparing for a future transition to AWS Glue.-- I've been deeply involved in designing, developing, and deploying APIs within AWS environments, leveraging a range of AWS services and best practices to build scalable, secure, and efficient solutions.--My experience includes the development of both RESTful and GraphQL APIs, focusing on creating robust interfaces for application components, facilitating seamless data exchange, and enabling the integration of complex systems. I've employed AWS API Gateway extensively to manage, deploy, and secure APIs, taking advantage of its features to monitor API activity, throttle traffic to prevent overuse, and handle API versioning to support different stages of development and production environments.--In terms of deployment, I've utilized AWS Lambda in conjunction with API Gateway to create serverless architectures, ensuring high availability and scalability without the overhead of managing servers. This approach has allowed me to focus on code quality and business logic, while AWS handles the infrastructure. I've also implemented CI/CD pipelines using AWS CodePipeline and AWS CodeBuild, automating the deployment process to enable rapid delivery of features and fixes with minimal downtime and ensuring consistent, error-free releases.--Security has always been a priority in my projects. I've implemented authorization and authentication mechanisms using AWS Cognito, ensuring that API access is securely controlled and that user data is handled in compliance with best practices and regulatory requirements.--Throughout my projects, I've made it a point to stay up-to-date with AWS advancements, continuously exploring new services and features to enhance API performance and reliability. This proactive approach has enabled me to deliver solutions that not only meet but exceed business and technical requirements.

Chicago, Illinois, United States

• Proficient in SQL Server and Oracle databases, with extensive experience in database administration, optimization, and SQL scripting.• Demonstrated experience in developing comprehensive data migration strategies from SQL Server and Oracle to AWS, ensuring data integrity, security, and minimal downtime.• Skilled in using Apache Spark for large-scale data processing and migration tasks, with a focus on utilizing Scala for Spark job development.• Proficient in Scala programming for data transformation and processing, leveraging functional programming paradigms for efficient data manipulation.• Experienced in deploying and managing Apache Spark clusters on AWS EMR, optimizing for performance and cost.• Designed and implemented robust ETL pipelines using Spark and Scala, ensuring efficient data extraction, transformation, and loading processes.• Utilized AWS Glue for serverless data preparation and loading, automating ETL processes and simplifying data integration tasks.• Expertise in migrating data to AWS data warehousing solutions, including Amazon Redshift, ensuring scalable and cost-effective data storage.• Implemented data lake solutions on AWS using Amazon S3, integrating with Spark and AWS Glue for flexible data processing and analysis.• Leveraged AWS Lambda for serverless computing tasks, including data processing triggers and automation of ETL workflows.• Developed real-time data processing solutions using Spark Streaming, integrating with AWS services for dynamic data analysis and insights.• Ensured data security and compliance with AWS IAM (Identity and Access Management), encryption, and key management practices during migration projects.• Used Amazon Athena for serverless querying, enabling quick insights from data stored in Amazon S3, with SQL-like querying capabilities.• Optimized Spark and Scala applications for performance and scalability, leveraging AWS EMR and auto-scaling features.

Tampa, Florida, United States

Implemented Hadoop data pipeline to identify customer behavioral patterns, improvingUX on banking website Develop MapReduce jobs in Java for log analysis, analytics, and data cleaning Perform big data processing using Hadoop, MapReduce, Sqoop, Oozie, and Impala Import data from MySQL to HDFS, using Sqoop to load data Developed and designed a 10-node Hadoop cluster for sample data analysis Regularly tune performance of Hive and Pig queries to improve data processing andretrieving. Skilled in leveraging Tableau to create visually compelling and interactivedashboards and reports, enhancing the analytical capabilities of business teams. Experienced in connecting Tableau to various data sources such as SQL databases, cloudservices, and spreadsheets, facilitating efficient data blending and visualization. Run Hadoop streaming jobs to process terabytes of XML data. Create visualizations andreports for the business intelligence team, using Tableau and Ingested data from RDBMSand performed data transformations, and then export the transformed data to MongoDB asper the business requirement. Wrote check code in Groovy to verify the correctness of map data. Analyzed failuresfound by the checks to determine exactly what was wrong. Assisted other developers withlearning Groovy and advised them on writing efficient code.  AWS Migrated Hive QL queries on structured data into Spark QL to improveperformance. Involved in improving the performance and optimization of the existing algorithms usingSpark. Developed Spark code and Spark-SQL/Streaming for faster testing and processing of data. Handled large datasets using Partitions, Spark in-memory capabilities, broadcasts inSpark, effective & efficient Joins, transformations. Well experienced in handling Data-Skewness in Spark-SQL. Implemented MLLIB in Spark and used K-means algorithm to cluster the data available inhive tables.

Bachelor'S Degree, Computer And Information Sciences And Support Services

Education record