Gogul Anbazhakan

• Own end-to-end analytics solutions, from data ingestion and transformation to data modeling and executive reporting.
• Design scalable cloud data warehouse architectures and self-service BI solutions using SQL, Python, AWS, Redshift, Tableau, and Power BI.
• Build and optimize high-performance data models, ETL pipelines, and analytical datasets supporting business-critical decision making.
• Drive data quality, governance, performance optimization, and CI/CD best practices across analytics platforms.
• Partner with product, engineering, finance, and business stakeholders to deliver actionable insights and KPI frameworks.

Key Project Highlights:

Pharmaceutical Data Platform Migration (AWS Redshift)

• Led a high-priority data migration project for a global pharmaceutical company, transitioning legacy reporting logic to a redesigned AWS Redshift platform.
• Developed and optimized Redshift Views and Materialized Views to replicate existing business logic while aligning with the new data model.
• Performed end-to-end data validation and reconciliation, ensuring report continuity, data accuracy, and zero business disruption.
• Quickly ramped up on a complex legacy environment and delivered critical migration components ahead of expectations.

WebFOCUS & Tableau to Power BI Migration

• Delivered enterprise report modernization for a leading U.S. railcar company by migrating WebFOCUS and Tableau reports to Power BI.
• Recreated complex report logic, calculations, filters, and interactive features while preserving the existing user experience.
• Migrated underlying data assets, including tables, views, and business rules, ensuring complete reporting accuracy.
• Conducted extensive validation and stakeholder testing to achieve seamless user adoption with minimal operational impact.

• Led multiple end-to-end Analytics Engineering, BI, and Data Platform initiatives for global SaaS, MarTech, Gaming, Subscription, E-commerce, and Trade clients.
• Architected and implemented scalable ETL/ELT pipelines using Apache Airflow, AWS MWAA, Python, Redshift, Athena, BigQuery, and Salesforce.
• Built enterprise data warehouses, dimensional data models, materialized views, and self-service analytics ecosystems serving Finance, Sales, Customer Success, Product, and Operations teams.
• Delivered executive dashboards and analytics solutions using Tableau, Power BI, Metabase, Holistics, and Looker.
• Reduced infrastructure and database costs by approximately $27K annually through performance tuning, query optimization, warehouse redesign, and operational improvements.
• Led client engagements, requirement gathering, solution architecture, project delivery, production support, and stakeholder management.
• Mentored junior engineers, conducted code reviews, and established BI development standards and best practices.

Key Project Highlights:

Enterprise Analytics Platform & Salesforce-to-Redshift Data Warehouse

• Designed and implemented a production-grade Salesforce → S3 → Redshift → Tableau analytics platform using Apache Airflow and AWS MWAA.
• Developed automated ETL pipelines, reconciliation frameworks, Slack alerting, and Row-Level Security (RLS) enabled dashboards.
• Delivered real-time revenue, product usage, customer success, sales funnel, and finance reporting solutions.
• Migrated Airflow workloads from Kubernetes POC to AWS MWAA production environment.

BI Platform Modernization & Cost Optimization

• Owned complete BI environment lifecycle including development, production support, performance tuning, monitoring, and incident management.
• Developed optimized analytical views, materialized views, and warehouse tuning strategies that significantly improved performance and reduced operational costs.

Holistics Analytics Performance Optimization

• Resolved dashboard performance issues on datasets containing billions of records in AWS Athena.
• Designed query models, pre-aggregated datasets, cluster datasets, and optimized data granularity to drastically improve dashboard responsiveness.
• Delivered campaign, subscription, registration, and revenue analytics with secure role-based access.

User Analytics & Product Engagement Insights

• Built analytics dashboards tracking user retention, monetization, gameplay behavior, membership adoption, and engagement metrics.
• Enabled product teams to make data-driven decisions around customer retention and revenue optimization.

Google Sheets → BigQuery → Looker Analytics Platform

• Implemented automated data ingestion and warehousing framework integrating dynamic Google Sheets data into BigQuery.
• Developed advanced SQL transformations, materialized views, and Looker dashboards supporting inventory, inflow, outflow, and operational analytics.

Sales, Product & Customer Analytics

• Designed scalable Power BI solutions with optimized star schema models, advanced DAX calculations, drill-through analysis, and customer segmentation.
• Delivered executive-level insights on customer lifetime value, product adoption, regional performance, and sales growth.

• Gathered business requirements and translated them into scalable BI solutions, KPIs, and reporting frameworks.
• Developed automated ETL workflows, reusable datasets, and interactive Tableau dashboards.
• Built secure reporting solutions with role-based access controls and automated refresh processes.
• Collaborated directly with business stakeholders to improve reporting efficiency and decision-making.

Key Project Highlights:

Salesforce Automated Reporting & Leadership Dashboards

• Replaced manual spreadsheet-based reporting with automated Salesforce-integrated Tableau reporting solutions.
• Developed ETL workflows using Tableau Prep Builder and delivered executive dashboards showcased during annual leadership reviews.
• Implemented multi-level Row-Level Security (RLS) and governed access management for enterprise users.

Postgres-to-Tableau Business Intelligence Platform

• Designed KPI frameworks, dashboard wireframes, automated data preparation workflows, and executive reporting solutions.
• Built Tableau Prep automation and Tableau Online reporting infrastructure to provide near real-time business insights.

• Performed large-scale exploratory data analysis (EDA), anomaly detection, and data quality validation for machine learning initiatives.
• Utilized Python, Pandas, NumPy, and Matplotlib to analyze large datasets and uncover actionable insights.
• Supported Data Science teams through feature analysis, data preparation, model validation, and parameter tuning activities.
• Delivered analytical reports that improved model performance and accelerated product development efforts.