Anand Sharma

• As Solution Architect Lead at PIMCO, I am responsible for leading the strategic development, roadmap, and implementation of a robust data platform tailored to optimize efficiency, enhance client service, and satisfy regulatory analytics requirements. Leadership has been critical in tackling complex data gravity challenges for PIMCO's $1.6 trillion assets under management, striking abalance between immediate and long-term business objectives.
• Streamline the process for vendor data acquisition, leveraging new data acquisition platform. Reduced data ingestion timeline from 6 weeks to 1 day
• Leads the team of VP engineers and subject matter experts, fostering a culture of excellence and innovation within theorganization. This approach includes working alongside teams across PIMCO to develop and maintain modern data platforms and business intelligence solutions that cater to the evolving needs of business.
• Responsible for managing and developing the infrastructure for data platforms, modeling, storage, and business intelligence, ensuring sustained high-quality service across the firm.

At Cerner, now a part of Oracle and the world’s largest publicly traded health IT company, I have played a key role in modernizing the data platform to enhance healthcare solutions across more than 25,000 facilities in over 35 countries. My efforts have been pivotal in transitioning from traditional ETL jobs to advanced data pipelines in a distributed environment, substantially modernizing the data handling capabilities.

Key Contributions:

• Data Lake Implementation: Set up Microsoft Azure Data Lake to manage large-scale data across structured, semi-structured, and unstructured datasets, enabling scalable data storage and access.
• Self-Service Data Infrastructure: Strategized and implemented a self-service data platform, focusing on data privacy and security through catalog definition and establishing robust data ingestion and reporting mechanisms.
• Streaming and Ingestion Pipelines: Developed and implemented real-time data stream platforms using Apache Kafka on Azure HDInsight clusters. I crafted Java connectors that facilitate seamless data flow between Azure Data Lake, MongoDB, and SQL Server. Furthermore, I engineered data ingestion pipelines that integrate technologies like Azure Data Factory, Dell Boomi, and Apache Sqoop.
• Data Processing and Visualization: Designed and developed data processing pipelines using Databricks Spark and Azure U-SQL, complemented by dynamic data visualizations in PowerBI and Tableau to facilitate insightful analytics and decision-making.
• Data Modeling: Executed logical modeling in Azure Analysis Services and physical modeling across HDFS, MongoDB, RDBMS, and MPP systems, ensuring optimized data structures for enhanced performance and scalability.

These initiatives have significantly advanced Cerner’s data platform, aligning with the broader objective of providing cutting-edge health IT solutions globally. Project includes: Modernization of real-time service, refactor implementation of Cerner’s Sales and Services data, Travel badge reward program, Client Helpdesk streaming

Led a project to automate the consolidation and standardization of PICS financial data, previously managed in Excel, to enhance accessibility and reporting efficiency. This initiative was sponsored by the Financial Planning and Analysis team, aiming to streamline reporting on year-over-year revenue, gross margin, and operating income across various business units.

Key Achievements:

• System Installation and Configuration: Executed the setup and configuration of OBIEE 11g to support advanced data analytics and reporting capabilities.
• Project Delivery Strategy: Developed and implemented a phased delivery plan to ensure smooth transition and minimal disruption to ongoing operations.
• Data Migration: Coordinated the migration of financial data from Excel to more secure and manageable PDF formats.
• Data Mart Development: Constructed a specialized data mart for OBIEE, facilitating efficient data handling and customized reporting.
• Enhanced Data Interaction: Designed and implemented write-back tables to allow for the manual addition of commentary and budget figures directly within the system.
• Integration with Hyperion: Established real-time data integration with Hyperion to ensure continuous access to up-to-date financial data.

This project significantly improved data management practices, enabling more accurate and timely financial analysis and decision-making.

Led the Pearson project to transition the executive dashboard from Excel to a standardized, automated system. This initiative was supported by the Financial Planning and Analysis team, which focuses on reporting year-on-year revenue, gross margin, and operating income across various business units.

Key Contributions:

• System Configuration: Handled the installation and configuration of OBIEE 11g and OBIA to enhance data visualization and analytics capabilities.
• Customization of BI Applications: Modified BI Apps for SDE and SIL mapping to tailor the analytics environment to specific business needs.
• Project Delivery Strategy: Developed a detailed plan for phased implementation to ensure smooth transition and integration with existing processes.
• Stakeholder Engagement: Collaborated closely with business units to refine requirements and facilitate effective change management.
• Data Warehouse Design: Engineered a data warehouse to support both project-specific and broader financial analytics requirements.
• Interactive Data Tables: Implemented write-back tables to enable manual entry of commentaries and budget figures directly into the system.
• Data Integration: Established real-time data integration with Hyperion for immediate access to financial data.

• The Oracle Billing team is initiating an initiative to integrate/automate all revenue recognition processes within Oracle (all project types, including FP/FT, T&M, long-term, and media spend, etc.). Also, the revenue recognition calculations use actual timecards for the percent of completion accounting treatment (unlike the present process, which runs out of the staffing plan of each project, even for past dates).
• Built dashboard to depict end to end-to-end revenue recognition process
• Dashboard helped reduce billing cycle time by 20%