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Ashok - BI Developer/DBA

[email protected]

Location: New York City, New York, USA

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PROFESSIONAL SUMMARY: Experienced Business Data Analyst and BI Developer with over 9+ years of expertise in delivering data-driven and AI-driven solutions, bridging the gap between technical and business teams, and driving decision-making across industries such as retail, healthcare, and banking. Skilled in requirement gathering and analysis, facilitating stakeholder workshops to define KPIs, business goals, and system requirements for analytics platforms and AI-driven workflows. Proficient in Tableau development (versions 2018.1 - 2023.2), creating interactive dashboards and reports with advanced filters, calculated fields, and dynamic visuals to provide actionable insights for strategic decision-making. Extensive experience in SQL query development and optimization for data extraction, transformation, and aggregation, supporting real-time analytics and high-volume reporting needs. Adept at Python scripting, leveraging libraries such as Pandas, NumPy, PySpark, and Scikit-learn for data preprocessing, ETL automation, and building AI models for predictive and prescriptive analytics. Hands-on experience with AWS services, including Redshift, Lambda, S3, and SageMaker, to build scalable data pipelines, store high-volume datasets, and deploy machine learning models. Leveraged AI techniques to develop predictive models for demand forecasting, customer segmentation, and churn analysis, seamlessly integrating results into Tableau dashboards (versions 2019.1 - 2023.2). Demonstrated expertise in QA testing, validating AI model outputs, ensuring data pipeline accuracy, and conducting end-to-end testing for production-ready deployments. Designed and implemented ETL workflows, automating data ingestion from CRM, ERP, and operational systems to streamline data preparation and enhance reporting accuracy. Developed robust data models (star and snowflake schemas) to integrate multi-source data for healthcare and retail analytics, supporting AI-based insights and seamless Tableau visualizations. Proven track record in role-based security implementation using Tableau Server (versions 2018.1 - 2023.2) and AWS IAM to secure sensitive data and ensure compliance with GDPR and HIPAA regulations. Built and deployed machine learning models on AWS SageMaker, enabling advanced analytics such as sales trend prediction and market opportunity optimization. Managed data scheduling workflows on Tableau Server (versions 2018.3 - 2023.2) and AWS Batch, ensuring consistent, automated updates for real-time analytics. Conducted training sessions and workshops to upskill business teams in utilizing Tableau dashboards and AI-powered analytics tools, improving decision-making capabilities. Strong communicator and cross-functional collaborator, delivering enterprise-grade analytics solutions by integrating AI capabilities, advanced reporting, and interactive dashboards within strict timelines. EDUCATIONAL DETAILS: MS in Systems Management (Information Systems) from Florida Institute of Technology, FL, USA in May 2018 TECHNICAL SKILLS Business Analysis Requirement Gathering, Gap Analysis, Stakeholder Workshops, Process Documentation, Compliance Frameworks Business Intelligence Tableau (versions 2018.1 - 2023.2), Power BI, Tableau Server (Publishing, Role-Based Access) Data Analytics Python (Pandas, NumPy, PySpark), SQL (Advanced Queries, Window Functions, Subqueries), Statistical Analysis Data Visualization Tableau Dashboards (Interactive Filters, Drill-Downs, Predictive Insights), Reports, Mockups, Wireframes Database Management AWS Redshift, SQL Server, Oracle, MySQL ETL and Data Pipelines Python ETL, AWS Lambda, SQL Procedures, Workflow Automation, Data Cleaning and Transformation AI and Machine Learning Predictive Models (Demand Forecasting, Churn Analysis), Prescriptive Analytics, SageMaker, ML Libraries Cloud Platforms AWS (Redshift, Lambda, S3, SageMaker) Quality Assurance Data Pipeline Validation, Dashboard QA, Testing AI Model Outputs, Performance Optimization Regulatory Compliance GDPR, HIPAA, RBI Guidelines, AML, KYC Project Management Agile Methodologies, Cross-Functional Collaboration, Documentation, Training, Change Management PROFESSIONAL EXPERIENCE: SEPHORA (REMOTE) JUNE 2022 TO PRESENT SR BI DEVELOPER/BDA PROJECT DESCRIPTION: The project aimed to revolutionize the decision-making process for a large-scale organization in the retail and e-commerce domain by building a unified, AI-driven analytics platform. The platform integrated disparate data sources, automated predictive and prescriptive insights, and provided advanced interactive dashboards, enabling real-time, strategic decisions across multiple business units. RESPONSIBILITIES: Collaborated with business stakeholders to elicit and document complex requirements for an enterprise-grade AI-driven analytics platform, ensuring alignment with the dynamic needs. Conducted gap analysis and translated high-level business goals into detailed functional specifications for predictive modeling, prescriptive analytics, and interactive dashboard development. Developed technical documentation, including system architecture diagrams, ETL workflows, and data pipeline mappings, for seamless collaboration between engineering and analytics teams. Authored user manuals and implementation guides for Tableau (2023.2) dashboards and AWS-hosted predictive analytics workflows to facilitate adoption across business units. Engineered innovative solutions to integrate fragmented data sources from ERP, CRM, and POS systems into a unified analytics pipeline using AWS Redshift, Python (Pandas, NumPy), and SQL. Optimized AI model outputs to provide actionable prescriptive insights by leveraging Python-based ML libraries and seamlessly embedding results into Tableau visualizations. Delivered technical presentations to stakeholders, explaining the architecture of the AI-driven analytics platform, including predictive and prescriptive modeling pipelines. Conducted interactive workshops to train business teams on leveraging Tableau dashboards integrated with live AWS-hosted datasets for real-time decision-making. Diagnosed and resolved performance issues in Tableau dashboards by optimizing underlying SQL queries and AWS data pipeline configurations. Reverse-engineered legacy data models to adapt them for integration with modern AI-driven workflows, improving overall platform compatibility and scalability. Created wireframes and prototypes for Tableau dashboards, showcasing predictive analytics outputs and KPI tracking tailored to retail and e-commerce business units. Iteratively refined mockups based on stakeholder feedback, ensuring alignment with UX/UI best practices and enterprise reporting standards. Automated complex data preparation workflows using Python (Pandas, PySpark) and AWS Lambda to preprocess unstructured data for AI and Tableau analytics pipelines. Developed and optimized SQL-based ETL processes to ensure data accuracy, integrity, and readiness for downstream predictive and prescriptive models. Designed robust star and snowflake schema data models in AWS Redshift to integrate multi-source data, enabling efficient querying and seamless Tableau visualization. Implemented AI-driven enhancements within data models to support advanced forecasting and optimization analyses. Developed interactive Tableau dashboards leveraging predictive and prescriptive insights, incorporating AI model outputs such as demand forecasts and churn predictions. Built dashboards with advanced parameters, dynamic filters, and drill-down capabilities, delivering actionable insights for strategic and operational decision-making. Authored and optimized complex SQL queries for advanced analytics, including multi-join operations, window functions, and subqueries, to support high-volume data processing for Tableau visualizations. Automated SQL query execution through AWS Step Functions and Lambda, ensuring real-time data availability across analytics pipelines. Designed Tableau reports showcasing AI-generated insights, such as sales trend forecasts and customer segmentation, integrated with AWS-hosted live data sources. Delivered comprehensive reports with visualizations of retail KPIs, including revenue performance, inventory levels, and customer behavior patterns. Implemented role-based security in Tableau Server (2023.2) and AWS IAM to restrict access to sensitive retail and customer data, ensuring compliance with GDPR and CCPA standards. Configured secure data encryption protocols for Tableau data sources and AWS storage layers to safeguard information at rest and in transit. Set up and managed automated data refresh schedules in Tableau Server (2023.2) using AWS Batch to handle large-scale retail and e-commerce datasets efficiently. Proactively monitored scheduling workflows and resolved pipeline failures to maintain uninterrupted reporting availability during peak business operations. Designed and developed Tableau dashboards using Tableau Desktop (2023.2), incorporating advanced calculations, AI-driven insights, and KPI visualizations tailored for decision-makers. Created highly interactive dashboards with live connections to AWS Redshift, enabling real-time exploration of sales, inventory, and customer data. Published Tableau dashboards to Tableau Server (2023.2), ensuring enterprise-wide access to real-time analytics with optimized load balancing for concurrent users. Automated publishing workflows and implemented version control to maintain consistency and reliability across Tableau Server deployments. Conducted comprehensive QA testing of Tableau dashboards and AWS-hosted analytics pipelines, validating SQL queries, AI model outputs, and data visualization accuracy. Coordinated with DevOps teams to deploy dashboards and pipelines to the production environment, ensuring seamless transitions from QA to live systems. ENVIRONMENT: Tableau Desktop (2023.2), Tableau Server (2023.2), AWS Redshift, AWS Lambda, AWS S3, Python (Pandas, NumPy, PySpark), SQL Server, ERP, CRM, and POS systems ,AWS-hosted ETL pipelines, Embedded AI-driven predictive and prescriptive insights, GDPR ABBVIE (REMOTE) MAY2021 TO JUNE 2022 SR BI DEVELOPER/DA PROJECT DESCRIPTION: The project aimed to develop a data-driven pharmaceutical sales intelligence platform for a large healthcare organization. It integrated data from CRM, ERP, and third-party market research tools, providing real-time insights into sales trends, inventory performance, and regional market analysis. Advanced Tableau dashboards built on AWS infrastructure allowed teams to forecast demand, optimize inventory, and refine sales strategies across multiple geographies. RESPONSIBILITIES: Conducted stakeholder workshops to identify pain points in current reporting workflows and captured user stories for developing Tableau-based solutions. Partnered with sales and operational leadership to collect and prioritize requirements for analytics and reporting, ensuring alignment with pharmaceutical business objectives. Produced technical documentation detailing data integration workflows, Tableau Server deployment steps (v2019.1 - v2021.4), and data security measures to ensure traceability. Created detailed business glossaries and technical reference guides to standardize terminology and bridge the gap between business users and data teams. Resolved integration challenges by implementing ETL processes using Python (Pandas, Boto3) and SQL, harmonizing data from CRM, inventory, and third-party APIs. Optimized Tableau workbook performance by restructuring data pipelines on AWS Redshift and reducing dependency on calculated fields within dashboards. Delivered solution walkthroughs for sales, operations, and marketing teams, demonstrating how Tableau dashboards could drive more targeted decision-making. Actively collaborated with cross-functional teams during project reviews, incorporating feedback to continuously enhance dashboard usability and relevance. Created Tableau wireframes and prototypes (using Tableau Desktop 2019.3 - 2021.4) to present key pharmaceutical KPIs, such as regional sales growth and market penetration rates. Iteratively refined wireframes to meet AbbVie s corporate design standards and to ensure alignment with the needs of executive leadership. Developed ETL workflows with Python and SQL to automate the transformation of raw sales and operational data from sources like CRM and ERP into an analytics-ready format. Implemented data pre-aggregation strategies within AWS Redshift to reduce processing overhead and improve dashboard refresh times. Designed highly normalized and denormalized data models in AWS Redshift to streamline data retrieval for Tableau dashboards. Built data views incorporating calculated fields to deliver business-critical metrics like revenue growth, inventory turnover, and market share. Developed interactive dashboards in Tableau (versions 2019.1 - 2021.4) to visualize pharmaceutical sales patterns, regional performance, and inventory optimization metrics. Enhanced dashboards with predictive models, enabling teams to forecast future demand based on historical sales trends and external market conditions. Authored SQL scripts for advanced analytical queries, including multi-level aggregations and partitioned windows, to power real-time Tableau visualizations. Automated data refreshes in AWS Redshift using SQL procedures, ensuring continuous availability of up-to-date insights. Created visually appealing Tableau reports for tracking product-level sales, customer acquisition trends, and inventory aging, tailored to AbbVie s pharmaceutical goals. Delivered segmented reports by geography and product category, enabling granular analysis of sales trends and customer behavior. Implemented Tableau Server (2019.1 - 2021.4) row-level security to restrict data access based on user roles, ensuring compliance with pharmaceutical data governance policies. Configured access controls in AWS to secure connections between Tableau dashboards and data sources, protecting sensitive sales and customer information. Automated Tableau extracts and data source refreshes on Tableau Server to support dynamic sales reporting, reducing manual intervention by operational teams. Monitored and maintained data scheduling pipelines to ensure reliable delivery of insights during critical reporting periods. Designed user-focused Tableau dashboards tailored for AbbVie s salesforce, allowing them to track key performance metrics such as territory performance and sales quotas. Integrated dashboards with AWS-hosted Redshift data warehouses to ensure real-time accessibility and responsiveness during presentations and sales planning. Published Tableau dashboards to Tableau Server (versions 2019.1 - 2021.4), optimizing load balancing and permissions for over 100 concurrent users. Established automated workflows for server deployment, ensuring consistent dashboard updates with minimal downtime. ENVIRONMENT: Tableau Desktop (2019.1 - 2021.4), Tableau Server (2019.1 - 2021.4), AWS Redshift, Python (Pandas, Boto3), SQL Server, pharmaceutical sales, inventory, and market research data, Tableau Server row-level security and pharmaceutical governance compliance, AWS-hosted analytics pipeline CARDINAL INNOVATIONS MAR2019 TO MAY2021 SR BI DEVELOPER/DA PROJECT DESCRIPTION: The project focused on designing and deploying a healthcare analytics platform for Cardinal Innovations to enhance operational efficiency and optimize service delivery. The platform integrated claims, patient, and provider data, automating key reporting processes and enabling actionable insights through interactive Tableau dashboards. RESPONSIBILITIES: Authored data dictionaries and user guides to facilitate smooth handover and adoption of the developed analytics tools. Documented detailed process flows and system architectures, including the integration of claims and operational data into Tableau dashboards (versions 2018.1 - 2018.3). Resolved inconsistencies in claims and provider data by developing SQL-based validation scripts to ensure data accuracy and compliance with healthcare standards. Designed automated workflows using Python and SQL to streamline repetitive data transformation tasks, significantly reducing manual effort. Conducted presentations for healthcare administrators to showcase interactive Tableau dashboards and demonstrate their value in improving patient and provider insights. Facilitated knowledge-sharing sessions with end-users to ensure they could effectively leverage Tableau dashboards for operational decision-making. Created wireframes for dashboards that visualized key healthcare metrics, including claims processing times, provider performance, and patient care outcomes. Used iterative feedback loops to refine mockups, ensuring alignment with Cardinal Innovations' operational goals and compliance requirements. Cleaned and transformed raw healthcare data, including claims, enrollment, and provider information, using Python (Pandas) and SQL to prepare it for analysis. Automated ETL workflows to aggregate data from multiple systems into a unified format for Tableau visualizations. Developed healthcare-specific data models to integrate claims, patient, and provider data, enabling efficient querying for Designed hierarchical models to support drill-down capabilities for metrics like patient demographics, provider efficiency, and service utilization. Developed Tableau dashboards (versions 2018.1 - 2018.3) with filters, trends, and dynamic charts to visualize claims processing, provider network performance, and service utilization rates. Created dashboards that highlighted compliance gaps, ensuring regulatory standards were consistently met. Wrote complex SQL queries to analyze claims data, including calculations for average processing times, reimbursement rates, and service utilization metrics. Optimized SQL scripts for performance, ensuring efficient execution of large-scale data operations for Tableau reporting. Created Tableau reports to monitor patient service trends, provider performance metrics, and claims accuracy, enabling informed decision-making. Delivered reports that allowed healthcare teams to identify and address bottlenecks in service delivery and claims processing. Implemented database-level encryption for sensitive data fields, ensuring compliance with HIPAA regulations. Automated data refresh schedules on Tableau Server to maintain up-to-date dashboards reflecting real-time claims and service utilization data. Established monitoring protocols to ensure data pipelines were reliable during high-demand reporting periods. Designed Tableau dashboards that provided healthcare teams with insights into patient outcomes, claims trends, and operational efficiency. Built intuitive dashboards with drill-down capabilities, enabling granular analysis of healthcare data by region, provider, or service type. ENVIRONMENT: Tableau Desktop (2018.1 - 2018.3), Tableau Server (2018.1 - 2018.3), Python (Pandas), SQL Server,Claims, patient, and provider data structured into healthcare-specific data models, HIPAA-compliant data validation, Automated ETL pipelines CITY NATIONAL BANK OF FLORIDA JULY2018 TO MAR2019 BI DEVELOPER/DA PROJECT DESCRIPTION: This project focused on enhancing visibility into customer deposit trends and branch-level performance by creating a centralized reporting system. The goal was to identify growth opportunities, improve branch efficiency, and enable targeted marketing strategies using Tableau dashboards and automated data workflows. PROJECT DESCRIPTION: Designed automated data transformation pipelines to standardize and cleanse data, ensuring readiness for analysis. Integrated data from CRM, branch operational systems, and transaction logs into a unified repository using SQL-based ETL workflows. Developed snowflake schema models to organize multi-source data, enabling efficient querying and analysis of customer deposit trends. Enhanced data quality by implementing validation rules to detect anomalies in transaction and deposit data. Created interactive Tableau dashboards to monitor customer deposit patterns, branch-level performance, and regional growth trends. Incorporated features like heatmaps and KPIs to highlight high-performing branches and identify potential underperforming regions. Implemented role-based security in Tableau Server to restrict access to sensitive financial data based on user roles. Ensured compliance with GDPR and AML standards by anonymizing sensitive customer data in analytics workflows. Optimized SQL queries and Tableau data extracts to improve dashboard performance and reduce load times by 25%. Automated dashboard refresh schedules using Tableau Server, ensuring real-time insights for executive decision-making. HDFC BANK LTD, INDIA JAN 2014 DEC 2016 BUSINESS PROCESS ANALYST RESPONSIBILITIES: Conducted end-to-end process analysis for loan approvals, account openings, and transaction monitoring, identifying inefficiencies and areas for improvement. Collaborated with branch managers and department heads to gather requirements for streamlining operational workflows in retail and corporate banking. Developed detailed process documentation, including flowcharts, SOPs, and user manuals, to standardize banking operations across branches. Created regulatory compliance reports and operational summaries for internal audits and submissions to the Reserve Bank of India (RBI). Redesigned customer onboarding workflows, reducing account opening time by 25% through process automation and redefined verification steps. Conducted time and motion studies to optimize loan processing cycles, improving turnaround time and enhancing customer satisfaction. Worked closely with IT teams to implement process automation tools, ensuring they met operational and compliance requirements. Acted as a bridge between business units and technical teams, translating business needs into actionable technical specifications. Analyzed transaction and operational data using SQL to identify bottlenecks, inefficiencies, and potential risks in daily processes. Used data insights to recommend changes in cash handling procedures, reducing discrepancies and improving reconciliation accuracy across branches. Assisted in implementing compliance frameworks to ensure adherence to RBI guidelines, including KYC and AML requirements. Monitored and reported on high-risk transactions and operational anomalies, mitigating potential risks through preventive measures. Spearheaded automation of repetitive processes, such as daily cash reconciliation and document verification, reducing manual errors and increasing efficiency. Collaborated on the implementation of automated reporting systems, providing real-time updates on key operational metrics for decision-makers. Analyzed customer feedback and transaction data to identify pain points, leading to enhancements in banking services and customer support processes. Proposed and implemented changes in branch workflows to improve queue management and reduce wait times for customers. Operational Efficiency Projects Prepared and submitted critical operational and compliance reports to RBI, including metrics on non-performing assets (NPAs) and suspicious transaction monitoring. Ensured all compliance-related processes were audit-ready, reducing the risk of penalties during regulatory inspections. Trained branch staff on updated processes and tools, ensuring smooth adoption of new workflows and maintaining operational consistency. Conducted workshops to improve team understanding of compliance frameworks and risk management protocols. Coordinated with multiple branches to roll out standardized processes, ensuring seamless integration of updates into daily operations. Acted as a point of contact for resolving operational queries and escalations from branch teams, ensuring timely issue resolution. ENVIRONMENT: SQL Server, process automation tools, regulatory compliance tools, Banking operations and transactional data,loan processing, account onboarding, and cash reconciliation, RBI guidelines, including KYC and AML frameworks. Keywords: quality analyst artificial intelligence machine learning user interface user experience business intelligence sthree information technology microsoft Florida