Ramakrishna Medisetti

• Design and implement enterprise BI architecture, including data pipelines, data modeling, and reporting layers.
• Collaborate with business stakeholders to understand analytics and reporting requirements.
• Lead the development of data warehouses, data marts, and analytics models.
• Architect and optimize ETL/ELT workflows using tools.
• Design robust and scalable data models using dimensional and normalized techniques.
• Define and enforce BI governance policies, including data quality, security, and compliance.
• Provide technical leadership and mentorship to BI developers and analysts.
• Evaluate and recommend modern BI technologies and platforms to meet evolving business needs.
• Create documentation and architectural diagrams for BI processes, solutions, and systems.
• Evaluated business requirements for data solutions, ensuring compliance with enterprise architecture guidelines.
• Designed data architecture frameworks to support business intelligence solutions.
• Implemented Looker to enhance data visualization capabilities with LookML, and worked on augmented analytics of Looker capabilities, such as Actionable Insights, Automated Alerting, Natural Language Query (NLQ), Embedded Analytics, and AI-Powered Analytics.
• Exposure to agent orchestration, stream analytics, or real-time ingestion, semantic layers concept, BI metadata modelling, or reusable KPI libraries.
• Lead innovation efforts involving AI/ML-driven insights, agent-based orchestration, and telemetry-enabled BI optimization.
• Familiarity with agent frameworks, GenAI orchestration, and prompt engineering for BI use cases
• Strong Data Storytelling capabilities around data value realization.
• Experience in launching, scaling, or governing enterprise analytics products and BI Observability, Telemetry, and performance tuning for large user bases.

As part of the One Verizon Data Strategy Program from the Enterprise Architecture team, I have contributed to the following key activities.

• For the EDW Migration project to move users and data from on-premise Teradata to Google Cloud Platform, which aims to improve trust in data, enable select real-time data feeds, improve the grain of data, unlock seamless data discoverability, enact frictionless data governance, enhance the performance of Verizon platforms, and enable data products after identified data assets are landed in GCP.
• Identify current EDW ecosystem challenges with legacy technologies, study the current landscape, and understand the footprint of existing technologies being used across LOBs to modernize and rationalize the tech stack and architecture process.
• High-level Solution Breakdown.
• GCP Resource Hierarchy: Organization Structure.
• High-level data strategy for end-to-end enterprise functional architecture for EDW modernization, with a blended approach of Data Fabric and Data Mesh to avoid scattered logic and data duplication (MVoT) by choosing a Unified Semantic Layer (SSoT).
• Solution design to define target state architecture for migrating from legacy on-premises Teradata technology to next-generation cloud-based technology within Google Cloud Platform.
• Technical Design Implementation Plan.
• EDW migration end-to-end stage gate process, which includes inventory analysis, data classification, cataloging, and datasets onboarding, design/build, unit test, and SIT readiness (synthetic data generation), SIT execution, and UAT readiness (data validation tool setup for A-B comparison between the current production system and the new migration system), build data products process, which are accessed through the data marketplace.
• Tool/technology recommendation process, which includes identifying key stakeholders for evaluation and high-level timelines, capturing enterprise requirements from stakeholders (RFI), conducting industry research, analyzing vendor RFI and demos, selecting vendor tools and POCs, and making recommendations to the leadership team for approval.
• Vendor technology evaluation process for ETL, Data Lineage, Data Quality, Data Observability, Change Data Capture, Metric Governance, Master Data Management, Semantic Metric Hub, Data Retention Planning, Test Data Management, Data Protection Implementation, and other critical areas.

• Technologies: Google Cloud Storage, BigQuery, BigTable, Cloud SQL, Cloud Spanner, Cloud Dataflow, Cloud Dataproc, Cloud Pub/Sub, Cloud Dataprep, Cloud Composer, Kubernetes, Dataform, Python, Machine Learning, Plx Suite, G3 Stack, Looker, Data Studio, and Tableau.
• Work with client teams to design and implement modern, scalable data solutions using a range of new and emerging technologies from Google Cloud Platform.
• Migrate on-premise infrastructure to GCP products such as Hadoop, Teradata, Oracle, and Hive.
• Build a Data Warehouse in BigQuery.
• Build orchestration for batch data loading using Cloud Composer.
• Build a Data Lake using Dataproc.
• Process streaming data with Cloud Pub/Sub and Dataflow.
• Visualize data for making data-driven decisions with Looker and Data Studio.
• Build machine learning solutions on GCP using Python.
• Experience with CI/CD to build robust data pipelines.
• Proven work experience in provisioning Infrastructure as Code (IaC) using Terraform.
• Integrate business validations with DataOps to make data operations at scale for finance.
• PLX suite expert and had experience with SQL readability for internal code review.
• Designed and implemented dashboards in Tableau, Plx, and Data Studio by connecting to the data sources.
• Good hands-on experience in the deployment process to move work files into the Codebase with the G3 Stack (Cider, Piper, and Critique).

• Technologies: Tableau, Google Cloud Platform.
• Analyze and understand requirements, perform data analysis, and work with business users on any clarification.
• Create datasets in Google BigQuery, and pull tables from these datasets to connect in Tableau Desktop.
• Design and develop reports and dashboards using Tableau Desktop.
• Publishing workbooks and dashboards from Tableau Desktop to Tableau Server.

• Technologies: MicroStrategy.
• Analyze and understand requirements, perform data analysis, and work with business users on any clarification.
• Design and develop reports and dashboards using MicroStrategy.
• Migration of projects from development to test to production environment.

• Technologies: MicroStrategy, SSIS.
• Analysis and understanding of the existing data model and data dictionary, business rules, existing reports, and BI component requirements; translate business requirements into technical design and specifications.
• Develop different types of visualizations, dashboards, using MicroStrategy.
• Migration of projects from development to test to production environment.

• Technologies: MicroStrategy, ODI, Netezza.
• Development and deployment of schema objects, application objects.
• Design and Development of Reports and Advanced Dashboards.
• Create intelligent cubes to increase the performance of reports.
• Work on MicroStrategy Office, Enterprise Manager, Integrity Manager, Command Manager, and Distributed Services.
• Migration of projects from development to test to production environment.

• Technologies: AutoCAD, MicroStation.
• Capturing data in the maps and capturing manholes, conduits, POIs, structures, terminal enclosures, etc., using the rulebook.
• If the data is missing, raise a query to the customer support team.
• Work on conversion, quality checking.
• Send the data to the cable team to do their work.