Data Professional with expertise in Machine learning model Development and efficient Exploratory Data Analysis. Extensive experience with orchestration of data pipeline, and Extract, Transform, Load. Professional underst…
Data Professional with expertise in Machine learning model Development and efficient Exploratory Data Analysis. Extensive experience with orchestration of data pipeline, and Extract, Transform, Load. Professional understanding of Data Warehousing and Data Modelling. Experienced in collaborating with multifunctional teams to translate system requirements into design specifications.
• Led end-to-end ownership of projects, from initial analysis to successful implementation, ensuring seamless data flow.
• Engineered and automated ETL processes using AWS Glue successfully transferring over 50 million records from diverse sources to AWS Redshift. This significant overhaul of database structure and granularity paved the way for streamlined business functions.
• Spearheaded the development and deployment of a real-time log analytics system using Kafka and Spark, enabling the team to monitor and optimize import-export operations dynamically.
• Enhanced SQL queries and ETL procedures, achieving a remarkable reduction in runtime by two hours for every million records in the production environment.
• Led the design and implementation of data governance practices in data modeling, ensuring data integrity, quality, compliance.
• Pioneered advancements in ETL processes and fine-tuned SQL operations, resulting in punctual and precise large-scale data processing. These significant contributions were recognized with a promotion to the position of Associate in just two years.
• Implemented data warehousing strategies including data mart construction, OLAP cube development, and data mining, facilitating efficient data analysis and reporting.
• Applying machine learning algorithms such as regression, classification, and dimensionality reduction to develop predictive models for optimizing import/export processes and forecasting demand.
• Employed data analysis techniques to optimize cross-border package transit times by an impressive 14.7%.
Led end-to-end ownership of projects, from initial analysis to successful implementation, ensuring seamless data flow.
Engineered and automated ETL processes using AWS Glue successfully transferring over 50 million records from diverse sources to AWS Redshift.
Spearheaded the development and deployment of a real-time log analytics system using Kafka and Spark, enabling the team to monitor and optimize import-export operations dynamically.
Enhanced SQL queries and ETL procedures, achieving a remarkable reduction in runtime by two hours for every million records in the production environment.
Led the design and implementation of data governance practices in data modeling, ensuring data integrity, quality, compliance.
Pioneered advancements in ETL processes and fine-tuned SQL operations, resulting in punctual and precise large-scale data processing.
These significant contributions were recognized with a promotion to the position of Associate in just two years.
Implemented data warehousing strategies including data mart construction, OLAP cube development, and data mining, facilitating efficient data analysis and reporting.
Applying machine learning algorithms such as regression, classification, and dimensionality reduction to develop predictive models for optimizing import/export processes and forecasting demand.
Employed data analysis techniques to optimize cross-border package transit times by an impressive 14.7%.
Orchestrated the consolidation and transfer of 1.5 million records from antiquated systems into Google Cloud's CRM solution, utilizing Google Cloud Dataflow.
Supervised the collecting and analysis of YouTube video consumer data, including categories, views, likes, dislikes etc.
Using Google Cloud Dataflow, we designed ETL (Extract, Transform, Load) pipelines to clean, transform, and store this data.
Developed and implemented data visualization techniques, including charts, graphs, and dashboards, to effectively communicate findings to stakeholders and team members.
This in turn increased auditor productivity by 10%.
Collaborated seamlessly with data scientists, analysts, content managers, stakeholders, aligning data-driven strategies harmoniously with overarching operational goals.
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