Experienced data and analytics leader with over eleven years of experience spanning hands-on project management roles with a strong background in Azure, AWS and GCP. Proven track record of delivering end-to-end enterpris…
Experienced data and analytics leader with over eleven years of experience spanning hands-on project management roles with a strong background in Azure, AWS and GCP. Proven track record of delivering end-to-end enterprise-level data solutions, defining and executing data strategy, and introducing and enforcing processes across fintech, health, telecommunication, and utility sectors. Adept at leading cross-functional teams, implementing and optimizing data platforms to propel data-driven decision-making and delivering actionable insights. Seeking a challenging leadership role in organizations committed to driving data excellence.
Data Strategy Development
Project Management
Cost Reduction & Scalability
Change Management
Mentoring & Team Management
Turned senior management’s vision into strategic roadmaps and led pods of teams in the successful design and implementation of data products for Fortune 500 companies and startups.
Led multiple client discoveries and deliveries by working with cross-functional teams of engineers, managers and executives to develop innovative enterprise data solutions to deliver value to businesses and customers.
Architected and developed phased implementation of data infrastructures and tackled challenging use cases for ML/AI integrations by leveraging tech stack including but not limited to AWS, Azure, Databricks, and Snowflake.
Managed constraints, assumptions, and risks and communicated effectively with stakeholders to ensure appropriate project scoping, goal setting, timelines, and deliverables.
Developed and executed large-scale migrations to move data from the on-premise legacy systems (i.e. Cloudera, etc) to the cloud (Azure, AWS, GCP, and Databricks).
Led the implementation of multiple accelerators across Azure and AWS to provision resources, ingest, process data and scale data observability, reducing development time and production release time for clients.
As a Solutions Architect, turned senior management’s vision into strategic roadmaps and led pods of teams in the successful design and implementation of data products.
● Led multiple client discoveries and program scale deliveries by working with cross-functional teams of engineers, managers and executives to develop innovative enterprise data solutions to deliver value to businesses and customers.
● Architected and developed multi-phased implementations of data infrastructures and tackled challenging use cases for ML/AI integrations by leveraging tech stack including but not limited to AWS, Azure, Databricks, and Snowflake.
● Managed constraints, assumptions, and risks and communicated effectively with stakeholders to ensure appropriate project scoping, goal setting, timelines, and deliverables.
● Collaborated with sales pursuits, business development, and delivery teams to develop RFPs and SOWs for large-scale data modernization and data migration projects.
● Developed and executed large-scale migrations to move data from the on-premise legacy systems (i.e. Cloudera, etc) to the cloud (Azure, AWS, GCP, and Databricks)
● Led the implementation of multiple reusable accelerators across Azure and AWS to provision resources, ingest, process data and scale data observability, reducing development time and production release time for clients.
Led a small team of data engineers for data lake and data infrastructure in an AWS environment to ensure data enablement, data governance, and data democratization throughout Wave.
Led and executed POCs using AWS tools and services to improve data ingestion, storage, processing, data quality and governance to scale with the increasing volumes and number of data sources.
Collaborated with the risk teams and ML teams to develop ML-based risk scoring models to identify fraud across various situations (onboarding, credit risk, transactions, etc.).
Audited data infrastructure systems and identified improvements to facilitate scaling of operations, resulting in an 85% reduction in incidents and a reduced incident recovery time.
Led the implementation of a next-generation data platform on AWS and incorporated real-time streaming data sources.
Built a data orchestration framework leveraging AWS Step Functions to improve data accuracy and integrity by enabling the management of dependencies, altering notifications, and retries to ensure timely and reliable data for the organization, thus meeting Wave’s strategic goals and objectives.
Served as SIM’s first BI and analytics Manager and led a high-performance BI team responsible for all data-related initiatives.
Managed team priorities, groomed backlog, and coordinated projects with cross-functional stakeholders.
Led design, development and rollout of data integrations in partnership with business stakeholders and vendors to ensure data flow between disparate systems (i.e. asset management, Oracle, Salesforce).
Led a small team of developers in architecture design, API design, and testing of a Windows tablet, desktop application and mobile application to enable digital transformation across SIM.
Authored and implemented SIM’s BI strategy to align all divisions and entities connected through M&A.
Provided project leadership and mentoring to the BI team.
Led the design and development of data warehouses and ETL processes using the Microsoft BI platform to support reporting and analytics from diverse systems (SaaS platforms and on-prem apps).
Developed KPIs and metrics roadmap with stakeholders across SIM to measure business and operational performance.
Led the upgrade of SSRS from 2008 to 2016 and redesigned 300+ SSRS reports, enabling report availability on mobile and leveraging new features for report visualization.
Executed POCs of various visualization tools; Introduced Power BI and developed 30+ reports to enhance data-driven decision-making capabilities across SIM.
Led a successful implementation and migration from legacy apps to Salesforce by participating in the planning, requirements gathering, cost analysis, development and roll-out.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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