SUMMARY:

• Over 15+ years of experience in data warehousing development with a strong background in many related aspects of this area of technology that range from designing complex POCs on multi - fact table star schemas that collect important BI KPIs - to developing industry-standard SSIS ETL and ADF packages that perform intricate data pulls and populate fact and dimensional tables from a variety of source systems - to complex data-driven production engineering constructs that dynamically partition large corporate cubes with DSO and AMO and Azure cloud integration solutions; experienced in setting up and migrating to Azure SQL Server Datawarehouse;
• Precision crafted front-end reporting solutions with Microsoft products utilizing expert knowledge of SQL, MDX and DAX languages with the latest Power-BI solutions including cloud-based SQL Azure and Azure Synapse
• Extensive IT experience in various industries has been gained by hands-on implementation of very large-scale BI projects as well as scaling complex BI pilots using the most current development paradigms; use of; AAD
• Expert in major Complex Financial Data Migrations and major Master Data Efforts; Author of 2 ETL frameworks;
• Expert in PowerBI Premium with incremental load and AutoML functionality and Administering Premium Capacity
• Azure and DataBricks notebooks performance improvements; authoring Databricks Spark-Jobs with SQL;
• Expert in translating complex SAP screens to JSON schema & data files consumable by bots and/or workflows;
• Expert in Postgre SQL and migration of on-prem data to AWS Redshift with custom code to ingest from S3
• Expert in modeling star and snowflake Data-Warehousing Solutions with SQL Server 2019 and Analysis Services 2019 (SSAS/Tabular) as well as previous versions: Expert In PowerBI and PowerBI embedded; SSAS 2016, SSAS 2014 and earlier, SSRS translating complex business requirements into valid scalable schemas, with Python; AWS Glue;
• Ultimate Complexity SQL Expert, extensive experience using with Cloud technologies: Azure Data Lake Analytics
• SQL Azure plus cloud-based Data warehousing solutions with SSAS/Tabular, Complex DAX metrics enablement;
• Data ETL SSIS 2017 (Expert in complex data migrations with fail-safe, multi-step data movement), Complex multi-level and multi-step auto data movement with multiple fail-safe flow mechanisms; authored an ETL Framework;
• Extensive experience developing advanced data movement with the use of complex SSIS Packages and ADF.
• Architecture of cubes and data-mart load of both SSAS 2014 and SSAS 2017, data-modeling with Erwin 10.1
• Expert in 50 Terabytes+ Cube Production Engineering - Author of data-driven partitioning constructs: Azure Data-Lake and Hadoop: Horton-Works HDC in Azure and Azure Data-Warehouse in Cloud; Azure Data Lake Analytics
• Data-Factoring SSIS packages into the cloud and designing cloud machine learning components & Attunity
• Expert Knowledge of Financial Reporting and Financial Close Procedures and Revenue Recognition with major ERP packages: Navision, SAP ECC and Peoplesoft, with SQL and Python doing data-movement; using Azure streaming;
• Large Database design both OLAP and OLTP (data-marts and subject areas) with experience migrating to Cloud.
• Extensive experience in programming T-SQLPL/SQL and writing complex stored procedures, complex relational and dimensional data modeling, DB2 SQL, Teradata SQL, Oracle PL/SQL; Cloud migrations of VMware to Azure Cloud
• Expert in Complex Solutions with MDX, DAX and multi-dimensional math modeling with MDX, DAX; Azure AD;
• Extensive experience with translating complex business requirements into multidimensional and tabular models.
• Hands-on Maintaining of Large Data-warehouses in RedShift, Scaling complex pilots to Azure Data-warehouses.
• Expert level understanding and experience with intricate data-design industry specific data-warehouse patterns, expert in redesigning ‘unworkable’ designs, your ‘models that work’ Expert; improving Databricks performance;
• AWS S3 storage setup, orchestration of AWS environment with Cloud-Formation component of AWS, JSON scripts expert and extensive knowledge of MongoDB as a repository for JSON files, HIVE programming and scripting.
• PIG for ETL and using PIG UDF functions in Python to extend PIG processing complexity, DevOps, TFS server.
• Microsoft Reporting Services reports with SQL, MDX and DAX, Power-BI and Data-Warehouse in Azure; Azure AD
• Auxiliary Accounting: GAAP, GL, AR, AP, cost-accounting, financial reports, cost allocation methodologies, Fixed and variable cost calculations, cost drivers, profitability analysis, forecast modeling, Operational Budgeting.
• Expert Azure DevOps: Heavy experience in setting up AWS environments using Terraform and AWS; VMware;
• Formation tools for the web, expert in narrowing agile code-to-productions deployment windows by fostering collaboration between teams of developers and using the most up-to-date TFS package-deployment facilities for code operations, effective use of these AWS cloud solutions for DevOps; Azure DevOps expert & Databricks;
• More than 20 years OLAP experience in Industries: Financial, HealthCare, Food, Mortgage, Manufacturing, Entertainment, Retail, Software Consulting, Government, Distribution, high-tech, subscription business.

WORK EXPERIENCE:

Confidential, Portland, OR

Azure Data Solutions Architect

Responsibilities:

• Lead NWN cloud migration effort at EY for the Assurance databases located across 35 datacenters all over the world and many other accessory data sources; performed deployments of Synapse DW;
• Developed standards for data movement for ADF data ingestion and retention;
• Providing Strategic Roadmap to NWN of the Data Migration effort to the cloud using the target as Synapse;
• Provisioned, configured and C/I deployed Azure ADF and Azure Gateways, storage and other necessary Azure components for the seamless ingestion of on-prem data-sources into the Azure cloud; administered all NWN Azure subscriptions; Azure Security Center; used ADF for upload of files to cloud;
• Created Synapse Workspaces, pools and tables; populated using dynamic ADF pipelines; manipulation of the data with ADF dataflows; creating aggregations and metrics; configuration of streaming data loads with Polybase & COPY; resolution of type I and type II issues for historical data reporting;
• Performing modifications of SQL Server on-prem DDL to fit the Synapse syntax; Provisioned, configured deployed and administered Azure Synapse Pool and Azure serverless resources ; deployed Azure DevOps with the help of ARM templates;
• Setup of Databricks clusters and administration of DB clusters; scheduling notebooks through ADF; improving Pyspark and Pandas code in the databricks notebooks; Azure Databricks for Data Governance;
• Handed complex query issues and improvement of the running of SQL queries in Synapse;
• Issue Technical Architecture Documents and thorough documentation of the Azure environment;

Confidential, Deerfield, IL

Sr. Azure Data Solutions Lead

Responsibilities:

• Architecting and directing PowerBI Reports and PowerBI Visuals and PowerBI Strategic Deployment; PowerBI dashboards and Azure SQL Server strategy for the Craniomaxillofacial (CMF) division of this Global Client; data-centric and special ‘case analysis’ frameworks POC and design to help streamline component CMF costs; design of a self-serve SSAS cube for this purpose; Designed an PowerBI Refresh API call scripts in PowerShell to trigger PowerBI refreshes; providing direction for backend tables and backend design components; PowerBI embedded; development of the SSAS ad-hoc Azure Service and cloud components: SSRS to PowerBI migrations, Info-path to PowerApps migrations; use of Azure DevOps for code rollout and stress-testing PowerBI reports; Databricks Notebooks to process ETL rules and upload and process files into the ADLS containers; custom rule notebooks;
• Created Synapse Workspaces, pools and tables; populated using dynamic ADF pipelines; manipulation of the data with ADF dataflows; creating aggregations and metrics; configuration of streaming data loads with Polybase & COPY; resolution of type I and type II issues for historical data reporting;
• Performing modifications of SQL Server on-prem DDL to fit the Synapse syntax; Provisioned, configured deployed and administered Azure Synapse Pool and Azure serverless resources ; deployed Azure DevOps with the help of ARM templates;
• Eliminated third party masking tool by using hashing technics in Spark/Python for downstream apps/users.
• Designed and implemented tracking in PySpark, error handling mechanism and email notifications.
• Developed terraform code to provision infrastructure in AWS and Azure; used ADO pipelines to deploy and used the module approach when writing the terraform code;
• Migration of data from S3 bucket to AWS Redshift using Postgre SQL with a driver table and dynamic SQL
• Wrote a custom Python solution for the Automated generation of Parquet files from on-prem SQL Server data sources using a driver table and auto-uploading of these files thereof to the ADLS; (available on my GitHub)
• Design and implementation of innovative Machine Learning (ML), Artificial Intelligence (AI) and Deep Learning (DL) solutions to solve challenging business and data analytics problems using Python & Spark (PySpark).
• Transformed and manipulated unstructured data (json) using pyspark, python pandas.
• Create data validation and ETL validation checks to ensure proper data flow. Used Attunity for replication.
• Writing pyspark and spark sql transformation in Azure Databricks to perform complex transformations for business rule implementation.

Confidential, Alpharetta, GA

Azure Data Solutions Lead

Responsibilities:

• Designed, coded and delivered a custom Azure Synapse Data Warehouse Solution for reporting for the analysis and reporting from multiple data sources including Maximo, API source and Beeline and others; migration of on-prem database objects to the Azure Synapse database; produced valid Synapse T-SQL code for native table (with appropriate distributions) and External tables; deployed Azure Synapse Spark Notebooks; setup Polybase and used it for the moving and manipulation of the Data stored in ADLS Gen2 (Azure Data Lake)
• Eliminated third party masking tool by using hashing technics in Spark/Python for downstream apps/users. components for the seamless ingestion of on-prem data-sources into the Azure cloud; administered one of the EY Azure subscription; worked with the Azure Security Center; used Attunity for upload of files to cloud;
• Created Synapse Workspaces, pools and tables; populated using dynamic ADF; manipulation of the data with ADF dataflows; creating aggregations and metrics; configuration of streaming data loads with Polybase & COPY;
• Performing modifications of SQL Server on-prem DDL to fit the Synapse syntax;
• Provisioned, configured deployed and administered Azure Synapse Pool with all accessory components such as Azure Key Vault, ADLS Storage and other Azure components as part of the rollout of the EY Cloud Data Retention area in the Cloud; configured Azure Security groups and the Azure Monitor;
• Designed, coded and delivered a custom Azure Synapse Accelerator utility for the automated migration of on-prem database objects to the Azure Synapse database; this included automatic production of valid code by way of a driver table in combination with sys tables that produced valid Synapse T-SQL code for native table (with appropriate distributions) and External tables; deployed Azure Synapse Spark Notebooks;
• Eliminated third party masking tool by using hashing technics in Spark/Python for downstream apps/users.
• Designed and implemented tracking in PySpark, error handling mechanism and email notifications.
• Developed terraform code to provision infrastructure in AWS and Azure; used ADO pipelines to deploy and used the module approach when writing the terraform code;
• Migration of data from S3 bucket to AWS Redshift using Postgre SQL with a driver table and dynamic SQL
• Wrote a custom Python solution for the Automated generation of Parquet files from on-prem SQL Server data sources using a driver table and auto-uploading of these files thereof to the ADLS; (available on my GitHub)
• Provided both strategic as well as detailed roadmaps to EY for all of the cloud data migration efforts and challenges.

Confidential, Allendale, NJ

Sr. Azure Solutions Engineer/ETL

Responsibilities:

• Architecting and directing PowerBI Reports and PowerBI Visuals and PowerBI Strategic Deployment; PowerBI dashboards and Azure SQL Server strategy for the Craniomaxillofacial (CMF) division of this Global Client; data-centric and special ‘case analysis’ frameworks POC and design to help streamline component CMF costs; design of a self-serve SSAS cube for this purpose; Designed an PowerBI Refresh API call scripts in PowerShell to trigger PowerBI refreshes; providing direction for backend tables and backend design components; PowerBI embedded; development of the SSAS ad-hoc Azure Service and cloud components: SSRS to PowerBI migrations, Info-path to PowerApps migrations; use of Azure DevOps for code rollout and stress-testing PowerBI reports; Databricks Notebooks to process ETL rules and upload and process files into the ADLS containers; custom rule notebooks;
• Working on a configured VDI using VMware and migrating of this environment to the Azure Cloud; Azure AD
• ADF for advanced data movement with U-SQL; Azure SQL Database or SSAS for the main data storage;
• Design and implementation of innovative Machine Learning (ML), Artificial Intelligence (AI) and Deep Learning (DL) solutions to solve challenging business and data analytics problems using Python & Spark (PySpark).
• Transformed and manipulated unstructured data (json) using pyspark, python pandas.
• Create data validation and ETL validation checks to ensure proper data flow. Used Attunity for replication.
• Writing pyspark and spark sql transformation in Azure Databricks to perform complex transformations for business rule implementation.
• SSAS move from on-prem to Azure Cloud SSAS; Azure Blob Storage for PBI Reports; configuration Notebooks
• Azure Data Lake Storage for archival and long-term comprehensive storage plus enablement ADLS of data movement from Data Lake into Azure SQL Synapse; Databricks notebooks and ETL rule engines;
• Development of ADF packages by way of SSIS runtime conversion; Salesforce Objects predicting leads and cross-sell; customer churn; Databricks ML feature tweaking; AWS AutoML for Redshift configuration;
• Azure Automation scripting for security and VM deployments using the ARM in PowerShell; PowerBI Refreshes with PowerShell; Setting up Azure HDInsight clusters with PowerShell;processing REST API’s with PowerShell;
• Wrote terraform for deployment of Azure infrastructure; deployed via YAML; deployed entire landing zone;
• Used Attunity for replicating on-prem data to the cloud and for file transfers;

Confidential, Washington, DC

Azure Solutions Engineer/ETL

Responsibilities:

• Designed, Architected and Implemented a Revenue Recognition data load Engine for satisfying SEC regulatory compliance requirements 605 and 606 for Confidential, complex technical requirements; Designed PowerBI Reports and effective visual PowerBI dashboards and PowerBI embedded components; PowerShell;
• Provided source code for balance data migration from the accounting system of record (Navision) to Oracle ERP Cloud, modules covered were: GL, Fixed Assets payables, receivables using SQL for ETL; automation; Databricks
• Architected a comprehensive ‘Product SKU mix’ (Type II history) data-prediction engine in PowerBI for product mix sell predictions; coded algorithms for calculated Fair Value(FV) for Revenue Recognition engine inputs; manipulate data using SQL and Python, Architected PowerBI approach; improving performance of Databricks;
• Provisioned the Azure Synapse Workspace in order to bring forth a SaaS solution for ingest and ML;
• Data Ingestion using PySpark, enrichment and presentation layer of various sources like ADLS, S3 and etc.
• Designed an ETL framework for efficient and automatic data-loading into the Rev-Rec system from Navision, resolved complex hierarchy issues for facilitating these loads, straight-line rev-rec; ingestion of data with ADF
• Configuring Virtual desktops with VMware Horizon; transferring the VM’s to the Azure Cloud; configuring Azure AD and transferring the on-premise AD to Azure with Azure AD Connect; setup of Cloud Administration and Security;
• Designed and provided a Finance cube with Power-BI reports all uploaded to the cloud which merged together two very complex source systems, uploaded source data to AWS S3 storage files and Data Pipeline AWS for data ingestions and customer churn data processing; coded complex SQL, wrote functions in Python to process and modify data, architected a PowerBI strategy; maintained Databricks notebooks; Matillion Jobs performance;
• Implemented PySpark on a cloud-based engineering tool - Azure Databricks stored large amounts of data in Azure Data Lake and performed analytics using Synapse;
• Using VMware with AWS to create a IaaS solution migrate VM to the AWS cloud; capacity plMware VDI’s; VMware Horizon; deploying services;

Confidential, Sterling, VA

MSBI Developer/ETL with Azure

Responsibilities:

• Developed and deployed a SSRS framework reporting against SAP ECC source system of Confidential, involved in modeling and prototyping a total SSAS cube solution (Analytics engine); PowerBI dashboards;
• Delivered 37 Financial reports as part of a Major Data Migration Effort to Microsoft Dynamics NAV for areas spanning GL ledger accounting, financial facility, long-term loan and other financial products, facilitated front and back office report integration into one cohesive solution using Microsoft Power-BI components, involved with dashboard prototyping with PowerBI using Navision as the source system of record, designed custom components for PowerBI reports for Dynamics NAV, Navision master data; configured Type II Dim for use in SSAS cube;
• Owned the BRD (business requirements document along with a BDG (business data glossary) reflecting business and technical definitions of all of the required element from the old and new systems as part of the data Migration effort and the requirements for the entire ETL processes, used SQL; coded type II history of the Product Dim;
• Use cloud-based Hadoop solution for batch processing and developed machine-learning solutions by integrating code from several systems, created AutoML modes in AWS with Hadoop and AWS RedShift as sources;
• Prototyped an incremental Data warehouse ETL architecture flow for backend nightly data pulls from source system and integrated a Power-BI executive dashboard solution, used SQL with Python UDF functions to enable the load into the data-warehouse backend that ran this dashboard, also used SQL for PowerBI report development;
• Developed an Databricks ML for ‘Customer churn’ prediction using AWS; suggested improvements to current model; developing Data Lake Proper Raw, Ingestion and Curated zones; proper setup of External Tables in Synapse;
• Used Informatica Cloud create data-movement packages and then schedule the ETL for uploading to cloud;
• Use of VMware to configure development Workstations; configuration of AD; setting up single sign-on; vRealize

Confidential, Washington, DC

ETL/Data Solutions Engineer

Responsibilities:

• Singlehandedly produced a Full-Functionality POC (proof-of-concept) solution on a High-Profile SAP to MSBI conversion project in 8 weeks flat, this involved producing a complex financial/budgeting 2014 SSAS prototype cube and a Power-BI front dashboard to demonstrate effective replacement of a portion of existing SAP ECC reporting for a large Government Organization (8th largest county in the US by revenue), existing solution was based on SAP BW and was developed over a long period of time, presented POC was for one module only - FM (Funds Management), Client was thrilled with proposed POC solution as presented and decided to expand to all of the other ECC modules (FM, GM etc.); configured and coded Type II historical dimension for the main government cost center dimension;
• Designed, reviewed, implemented and optimized data transformation processes in the Hadoop ecosystems including developing Python scripts to parse the raw data, populate staging tables and store the refined data in partitioned tables in the EDW, migrated existing SSIS packages to data-factory cloud; designed PowerBI reports;
• Served as Chief ETL Architect and Developer and technical lead for the SQL side of the ETL processing that populated the data warehouse and the SSAS Cube, authored all of the stored procedures that populated the cube. Served as Chief Cube Designer and worked with the Budget Reporting Group users to enhance and advance the usability of the SSAS cube from POC stage phase to full Production phase which involved directly collecting requirements in real-time, coming up with solutions/ways of implementing new features, created apps and ADD in Azure to register the app in Azure; created PowerBI dashboards and advanced PowerBI automations;
• Developed an Proof-of-concept mining model in SSAS to predict the ‘cash on hand’ minimum throughout Nov-July months of the year; developed Proof-of-concept mining model in SSAS to predict contract features most likely to influence ‘winning bid’ for the historical bids on existing government contracts below $1m;
• Administering the client VMware environment configuring Horizon server; adding resources to VDI desktops;

Confidential, Philadelphia, PA

MSBI Developer

Responsibilities:

• Helping Confidential move their existing physical data warehouses into the cloud space (Azure).
• Authoring the SSAS cube and backend (table) design for a comprehensive Member Analytical Engine to be used for advanced member/prospect segmentation and full ad-hoc costing analytics engine with capabilities to include advanced analysis of the following areas: patient utilization analysis, prospect lift analysis, treatment effectiveness analysis, provider rankings with special concentration on costing; coded Type II historical analysis for the main cost structures in the Provider dimension;