SUMMARY

• 17 years of solid working experience in IT industry with a PhD from University of Waterloo.
• 12 years of experience as a hands - on Solutions Architect/ Team Lead/ Specialist/ Developer in Big Data, Business Intelligence (BI), Data Warehousing, and multi-tiered applications in Java, and Scala.
• Expert in Machine Learning and Data Science, utilizing advanced analytics, artificial intelligence and cognitive services. The solutions include prescriptive (recommendation) and predictive analytics, sentiment analysis, text analytics, vision/image processing, and speech recognition, classification, pattern recognition, and regression.
• A full stack solutions architect at enterprise scale. Proficient in end-to-end design spectrum: developing business value justification and strategy, selecting and managing a technology vendor, designing a solution blueprint, envisioning the roadmap, team building, implementation, solution sustainment and DevOps.
• Defined the data governance strategy, designed cyber security patterns, implemented data standards and procedures across the enterprise; drafted business specific methodology to establish business stakeholder-driven data stewardship through MDM
• Led EDW projects on Massively Parallel Processing (MPP) Data Warehouse/ Data Lake Appliances such as IBM Netezza, Teradata, APS (PDW), Oracle Exadata, Customer MDM, Product MDM, DQ Framework.
• Expert in Enterprise Information Management (EIM) for retail operation. Designed various BI solutions including loyalty programs, card management, POS data management, customer behavioral analysis, store dashboards, finance, ecommerce, and cyber security analytics.
• Migrated 10s of applications and solutions to the Cloud using Azure, Google Cloud (GCP), Amazon AWS, IBM ICP.
• Extensively working on SQL Server 7 to 2016, Oracle, SQL, T-SQL, SSIS, SSRS, SSAS, OLTP, OLAP, Multidimensional Cube, MDX, PowerPivot, Tabular Model, SharePoint, PerformancePoint.
• Demonstrated experience and understanding of the best practices in all aspects of data warehousing (Inmon/Kimball approach). Solid experience in Data Warehouse Development Lifecycle (SDLC) including system analysis, design, implementation, testing, deployment, and maintenance.
• Strong knowledge and proven results in Data Warehouse, Data Mart, and Data Lake design including Dimensional Modeling (Star & Snowflake Schemas), ER Modeling, 3 Normal Forms, Normalization and Demoralization, Logical Model and Physical Model, Fact/Dimension/Hierarchy identifications.
• From Business Case to Data Visualization, I have designed and developed solutions by combining Business Process with Information Technology.
• Years of design and hands on experience in application development using .NET and Service Oriented Architecture (SOA)
• Authored numerous best practices, technical reports, processes & workflows, and methodology documents to standardize implementation, support infrastructure and sustainment teams, and to promote knowledge sharing. Coached and trained development teams in utilizing the BI framework.

PROFESSIONAL EXPERIENCE

Senior Big Data and BI Lead / Solutions Architect

Confidential, San Diego, California

Responsibilities:

• Led Big Data and BI projects to analyze data for a $100 Billion investment, managed by OMERS (Ontario Municipal Employees Retirement System). The projects ingest, transform, and analyze data for Capital Market, Private Equity Market, and Pension investment management. Created a big data framework architecture and implemented solutions using Azure Cloud, Azure Data Lake Store, Azure Data Lake Analytics, HDInsight (Managed Hadoop), Machine Learning Studio, Azure Data Factory, Azure Data Warehouse, Azure Analysis Services, Azure Data Catalog, and Power BI. I also performed stream analytics using machine learning anomaly detection for cyber security outages using Azure Stream Analytics.
• Designed and developed a Big Data project utilizing Spark, Kafka, Java, Cloudera, Hadoop, Hive, Impala, Flume, Sqoop, Map/Reduce, and Pig. The project collects information from capital market, performs advanced analytics for risk management. Subsequently, the unstructured data is processed to feed the BI layer.
• Designed solution, performed data modeling, and automated the data flow for Cyber Security and Incident Management System (ServiceNow) by running U-SQL scripts on Azure Data Lake and scheduling the data pipelines using data factory. Provisioned Azure environments by using Azure PowerShell and Resource Manager to manage the resources.
• Successfully installed and deployed an entire IBM Cloud Private ICP Cluster then implemented and deployed ELK Elasticsearch, Logstash, Kibana, Filebeat, Kafka, Zookeeper, Cassandra, Curator on ICP IBM Private Cloud, Kubernetes, Pods using Helm Charts, Scala SBT. IBM Cloud and IBM Cloud Private (ICP) is a Distributed Container based Architecture, Docker, Docker CLI, Kubernetes, Kubernetes CLI, Pods, Pods deployments. Service Deployments, Ingress, Helm Charts, Helm Charts CLI.

Senior Big Data / BI Solutions Architect

Confidential

Responsibilities:

• Designed and developed a Big Data project on Teradata utilizing Spark, Kafka, Java, Hortonworks, Hadoop, Hive, Impala, Flume, Sqoop, Map/Reduce, and Pig. The project collects information from cameras and sensors installed on the highways, performs advanced analytics to capture the information.
• Led BI/DW projects for Ontario's driver examination services. The solution consolidates the information from 55 Drive Test centers as well as 39 travel point locations. Designed the full stack BI solution including ETL, Staging, DW, Dashboard, and reporting layer in Power BI.
• Designed and developed an advanced analytical solutions that utilizes Machine Learning and Deep Learning frameworks for Ontario's driver examination services. The solutions utilize tools such as Machine Learning Studio, DLVM, R Server, Python, Jupyter notebooks, Azure Data Lake, Azure SQL database and many other data science and ML tools.
• Analyzed and prepared various datasets, ingested them into Azure, built data model, and applied various Machine Learning algorithms to find the most important parameters impacting the wait time at the centers and to predict the wait time at the centers. These algorithms include regression, Two-class classification, Multi-class classification, and anomaly detection. I also performed What-If analysis, proposed actions to be taken to reduce the wait time.
• Designed and developed Artificial Intelligence (AI) applications with Natural Language Processing (NLP) - With Cognitive Services API's. The solution include text analytics, Vision, and Speech recognition. The project collects information from cameras and sensors installed on the highways, performs advanced analytics to capture the information. Subsequently, the unstructured data is processed to feed the BI layer.
• Designed and developed fast scalable search system using a multicloud solution with Azure and AWS utilizing ElasticSearch for incident and ticket management. The high speed search gets its data from a Machine Learning system with Key Phrase extraction capabilities. Subsequently, user can search and perform text mining through unstructured text in a large scale data source.
• Established a roadmap for migrating legacy information warehouse to a modern high performance data warehouse running on multiple DW appliances. Drafted a BI/DW prioritized implementation roadmap while taking input from organization, business, and IT strategy documentation
• Created high-level architecture, solution blueprints, technology infrastructure implementation plan, integration plan, and disaster recovery plan. Created architecture artifacts and provided subject matter expertise in support of a technology selection process.