Rahul Agarwal

Innovative Solution Architect with in-depth understanding of software deployment and system design illustrated over 14 years of experience in similar roles. Excellent communication skills and extensive experience working with clients and partners.

• 2023, Data Asset Dashboard, The Analytical Dashboard project aims to create a user-friendly tool that allows users to track data variations over time. It offers advanced filtering capabilities, allowing users to search and analyze data based on various criteria and features. The dashboard also provides graphical representations of data trends across different timelines, enhancing data visualization and insights. This project aims to empower users with the tools and insights needed to make data-driven decisions and uncover valuable trends within their datasets., Python, Django, AWS, jQuery, HTML/CSS, Redshift, Postgres, Redis, Dockers, CI/CD
• 2023, Backbone V2, Backbone Version 2 is a significant upgrade to the organization's centralized 3rd party data resource. The project aimed to address issues in the older version, reduce pipeline processing time, eliminate data duplication, and introduce new features and optimizations. This upgrade provides a more efficient, reliable, and feature-rich centralized data resource, making it a significant step forward in data management and access., Python, Django, AWS, jQuery, HTML/CSS, Airflow, Redshift, Postgres, Redis, Dockers, CI/CD, Snowflake
• 2022, Media Onboarding Platform, The Audience Management and Campaign Automation Application project aimed to streamline the management of audiences and campaigns for an organization. Previously, the organization used a costly third-party tool, which provided limited insights. The project involved building an in-house application to upload audiences directly onto platforms, resulting in cost reduction, faster audience availability, and improved auditing capabilities. This project improved operational efficiency and enabled the organization to execute successful advertising campaigns with greater control, speed, and cost-effectiveness., Python, Django, AWS, jQuery, HTML/CSS, Airflow, Redshift, Postgres, Redis, Dockers, CI/CD, MongoDB
• 2022, Pella Automation, The Automated Report Generation Pipeline project streamlines the report creation process by implementing automated pipelines. This reduces the time needed to generate reports from weeks to hours, eliminates manual errors, and enhances overall efficiency. The project not only improves the accuracy and efficiency of report generation but also contributes to improved business operations by providing timely and reliable insights to clients., Python, Spark, Pandas, AWS, Airflow, Redshift, Dockers, CI/CD
• 2021, Experience Score, The Conversation Score Generator project is a deep learning model that evaluates and generates conversation scores for customer interactions between customers and business executives. This project is crucial for businesses in customer support and communication, as assessing the quality and effectiveness of conversations is crucial. By quantifying the quality of conversations and taking proactive measures to improve them, businesses can deliver better customer experiences, align customer service efforts with expectations, and ultimately improve customer loyalty and retention. The project's impact is significant, particularly in contexts where assessing the quality and effectiveness of conversations is crucial., Python, Spark, Django, jQuery, HTML/CSS, Pandas, AWS, MySQL, Dockers, CI/CD, TensorFlow
• 2019, BirdLake, The BirdLake Internal Data Lake project is an internal data infrastructure designed to efficiently manage and utilize data within an organization. It extracts data from various sources using pipelines built on technologies like Apache Airflow and PySpark, transforms the data into a normalized format, and stores it in a columnar database. The project generates key performance indicators (KPIs) required by stakeholders, which can be accessed via REST APIs on a user interface (UI) platform. The automated KPI generation and REST APIs provide real-time insights into business performance, enabling data-driven decisions. The project promotes data quality, security, and governance, ensuring the organization's data assets are reliable and compliant with industry standards., Python, Spark, Pandas, AWS, MySQL, Dockers, MongoDB, Bigdata, Redis, CI/CD

• 2023, Data Asset Dashboard, The Analytical Dashboard project aims to create a user-friendly tool that allows users to track data variations over time. It offers advanced filtering capabilities, allowing users to search and analyze data based on various criteria and features. The dashboard also provides graphical representations of data trends across different timelines, enhancing data visualization and insights. This project aims to empower users with the tools and insights needed to make data-driven decisions and uncover valuable trends within their datasets., Python, Django, AWS, jQuery, HTML/CSS, Redshift, Postgres, Redis, Dockers, CI/CD
• 2023, Backbone V2, Backbone Version 2 is a significant upgrade to the organization's centralized 3rd party data resource. The project aimed to address issues in the older version, reduce pipeline processing time, eliminate data duplication, and introduce new features and optimizations. This upgrade provides a more efficient, reliable, and feature-rich centralized data resource, making it a significant step forward in data management and access., Python, Django, AWS, jQuery, HTML/CSS, Airflow, Redshift, Postgres, Redis, Dockers, CI/CD, Snowflake
• 2022, Media Onboarding Platform, The Audience Management and Campaign Automation Application project aimed to streamline the management of audiences and campaigns for an organization. Previously, the organization used a costly third-party tool, which provided limited insights. The project involved building an in-house application to upload audiences directly onto platforms, resulting in cost reduction, faster audience availability, and improved auditing capabilities. This project improved operational efficiency and enabled the organization to execute successful advertising campaigns with greater control, speed, and cost-effectiveness., Python, Django, AWS, jQuery, HTML/CSS, Airflow, Redshift, Postgres, Redis, Dockers, CI/CD, MongoDB
• 2022, Pella Automation, The Automated Report Generation Pipeline project streamlines the report creation process by implementing automated pipelines. This reduces the time needed to generate reports from weeks to hours, eliminates manual errors, and enhances overall efficiency. The project not only improves the accuracy and efficiency of report generation but also contributes to improved business operations by providing timely and reliable insights to clients., Python, Spark, Pandas, AWS, Airflow, Redshift, Dockers, CI/CD
• 2021, Experience Score, The Conversation Score Generator project is a deep learning model that evaluates and generates conversation scores for customer interactions between customers and business executives. This project is crucial for businesses in customer support and communication, as assessing the quality and effectiveness of conversations is crucial. By quantifying the quality of conversations and taking proactive measures to improve them, businesses can deliver better customer experiences, align customer service efforts with expectations, and ultimately improve customer loyalty and retention. The project's impact is significant, particularly in contexts where assessing the quality and effectiveness of conversations is crucial., Python, Spark, Django, jQuery, HTML/CSS, Pandas, AWS, MySQL, Dockers, CI/CD, TensorFlow
• 2019, BirdLake, The BirdLake Internal Data Lake project is an internal data infrastructure designed to efficiently manage and utilize data within an organization. It extracts data from various sources using pipelines built on technologies like Apache Airflow and PySpark, transforms the data into a normalized format, and stores it in a columnar database. The project generates key performance indicators (KPIs) required by stakeholders, which can be accessed via REST APIs on a user interface (UI) platform. The automated KPI generation and REST APIs provide real-time insights into business performance, enabling data-driven decisions. The project promotes data quality, security, and governance, ensuring the organization's data assets are reliable and compliant with industry standards., Python, Spark, Pandas, AWS, MySQL, Dockers, MongoDB, Bigdata, Redis, CI/CD