Salim Hamdallah

• Managed and led organization wide BI 2.0 Transition Plan taking internally outdated data analytics processes and practices to new industry standard based on AI & ML trends.
• Used business objects, business intelligence and other reporting tools to extract data from data solutions and data warehouses.
• Leveraged text, charts and graphs to communicate findings in understandable format.
• Developed and implemented data collection systems and other strategies to optimize statistical efficiency and data quality.
• Performed root-cause analysis on data-related system problems to recommend or execute corrective action.
• Established and enforced project timelines and deadlines.
• Identified, reviewed and evaluated data management metrics to recommend ways to strengthen data across enterprise.
• Devised and deployed predictive models using machine learning algorithms to drive business decisions.

Senior Data Architect/Consultant: Mondelez International Inc.

• Implemented platform wide, revenue and loss driven collection of dashboards for senior leadership at Mondelez to assess, track and gain insights into Perfect Store data, revenue figures, waste numbers and performance across the entire platform in Salesforce's CRM Analytics Platform (Tableau based).
• With a highly sophisticated, well-rounded solution that provides data ingestion model and data transformation architecture to feed Perfect Store, revenue & waste figures, historical and trend data across the entirety of the platform and its respective segments.
• Led and facilitated requirements gathering and design workshops to outline dashboard design with senior clients
• Led and managed two offshore teams with total head count of 8 developers and testers
• Delivered 8 dashboards, 10+ recipes and dataflows, data ingestion scheduling and 8+ datasets
• ETL architecture built for Intelligent Recommendation data to be surfaced in one-of-a-kind Profitability Calculator dashboard
• ETL Architecture unification via GoogleBigQuery to CRM Analytics platform with efficient ingestion/sync times via optimized data mapping, data structure and data security.
• An entire data pipeline that is able to process over 2B rows of data in just 4 hours on a daily and weekly basis.
• Data export pipeline to CG Mobile app and Salesforce to surface revenue, waste and Perfect Store KPIs.

Senior Data Consultant/SME: Apple Inc.

• Roadmap strategy to optimize Insights Engine using best practices
• Conversion strategy from rule-based insights to an automated AI/ML driven Insights Engine
• Crawl, Walk, Run assessment for Apple existing D360 platform for big data, dashboards and digital user experience
• Detailed Technical assessment for Apple existing data architecture and data governance practices
• Technical roadmap strategy outlining data architecture changes to house Insights Engine 2.0 and downstream data impacts

Data Architect/Consultant: Marriott International

• Implemented platform wide, data, usage and metric driven collection of dashboards for senior leadership at Marriott to assess, track and gain insights into adoption and usage across the entire platform.
• With a highly sophisticated, well-rounded solution that provides data ingestion model and data transformation architecture to feed adoption scoring, engagement levels, historical and trend data across the entirety of the platform and its respective segments.
• Led and facilitated requirements gathering and design workshops to outline dashboard design with senior clients
• Led and managed team of 4 from Offshore and ran testing scripts and coached through dev tasks
• Built an entire Engagement Score system purely in TCRM without SF Apex or custom coding in SF
• Delivered 5 dashboards, 15+ recipes and dataflows, data ingestion scheduling and 25+ datasets in a span of just 4 months

Data/Business Analyst: Labcorp Inc.

• Provide valuable insight into client data driven by Einstein Analytics via Salesforce. Predictive analytics and historical metrics and reporting capabilities. Via creation of dataflows/recipes and datasets.
• ETL of data from Amazon S3, SFDC Local objects to construct dashboards, trends and reports.
• Bridge knowledge gap between functional business requirements to technical development end. Ingestion processes, dataset management processes, security and access implementations, and visualization/dashboard creation to ensure compelling and aesthetically pleasing 'storytelling with data'.