Data-Driven Solutions Architect for Cloud Analytics

Venkata Rama Krishna

Columbus, Ohio State +* (***) 241 – 5072 ***********@*****.*** LinkedIn

Professional Summary

Dynamic Solutions Engineer with a strong background in data engineering, analytics, and AI—transforming enterprise systems into intelligent, scalable solutions. Proven success in modernizing legacy data warehouses into Databricks Lakehouse architectures, optimizing cost and performance by up to 60%. Experienced in machine learning, MLOps, and real-time data pipelines, delivering measurable business impact across finance, healthcare, and e-commerce. Recognized for combining technical depth with business insight to drive data-driven innovation, efficiency, and growth across global organizations. Technical Skills

Cloud & Data Platforms: Databricks Lakehouse, AWS (S3, EC2, Lambda), Azure Data Lake, GCP BigQuery, Snowflake, Delta Lake, Unity Catalog, Delta Sharing

Programming & Scripting: Python, SQL, PySpark, Scala, Shell Scripting Data Engineering & ETL: Delta Live Tables (DLT), Apache Spark, Auto Loader, Airflow, DBT, Kafka, Structured Streaming, ETL/ELT Pipelines Machine Learning & AI: MLflow, scikit-learn, TensorFlow, PyTorch, Model Registry, Model Serving, RAG (Retrieval-Augmented Generation), Vector Search, LLMs (DBRX, Open Source)

Analytics & BI Tools: Databricks SQL, Tableau, Power BI, Excel (VBA), Superset, Looker Statistical Analysis & Modeling: Regression, Classification, Clustering, Time Series Forecasting (ARIMA/SARIMA), A/B Testing, Hypothesis Testing, Bayesian Analysis, Feature Engineering, Model Evaluation (ROC, AUC, KS, PSI) MLOps & DevOps: MLflow Pipelines, Docker, Git, CI/CD, REST API Integration, Monitoring & Logging, Model Deployment Automation Data Governance & Security: Unity Catalog, IAM/SSO, Row/Column-Level Security, Data Lineage, Compliance (Finance, Healthcare) Optimization & Performance: Photon Engine, Query Optimization, Cost Reduction, Pipeline Scaling, Performance Tuning Tools & Frameworks: Jupyter, VS Code, GitHub, Jenkins, Confluence, Jira, SAP Certifications: CPIM Lean Six Sigma Green Belt Tableau Data Analyst Certification Professional Experience

Solutions Engineer Databricks – USA May 2023 – Present

● Spearheaded enterprise-wide modernization of legacy data warehouses to the Databricks Lakehouse Platform, unifying data engineering, analytics, and AI workflows across multiple business domains.

● Conducted comprehensive architecture assessments of pipelines, SLAs, and BI systems; delivered a 30/60/90-day migration plan with risk analysis, cost optimization, and ROI projections.

● Architected and deployed scalable Lakehouse environments using Delta Lake (Bronze–Silver–Gold) layers, Auto Loader for ingestion, and Photon for 40–60% performance improvement and cost reduction.

● Designed and implemented automated ETL pipelines using Delta Live Tables (DLT) with Expectations to enforce data quality and lineage tracking, reducing operational incidents by over 50%.

● Established observability and recovery frameworks, authoring detailed runbooks and operational documentation to standardize long-term maintenance.

● Delivered real-time analytics pipelines using Structured Streaming and Auto Loader, implementing stateful processing, watermarking, and checkpointing to achieve sub-minute latency and 99.9% pipeline uptime.

● Built Databricks SQL dashboards for live operational monitoring and anomaly detection, empowering business teams with actionable, real-time insights.

● Engineered a complete MLOps lifecycle leveraging MLflow, Model Registry, and Model Serving to automate experiment tracking, versioning, deployment, and performance monitoring.

● Deployed REST API endpoints for model inference, ensuring reproducibility, low-latency performance, and governance compliance.

● Implemented enterprise-wide data governance through Unity Catalog, defining catalog–schema–table hierarchies, row/column-level security, and IAM/SSO integration for compliance with security policies.

● Defined cluster policies and enabled secure external data sharing via Delta Sharing, enabling collaboration across regulated sectors

(finance, healthcare, and public sector).

● Developed and deployed an enterprise-grade RAG (Retrieval-Augmented Generation) solution using Databricks Vector Search and LLMs (DBRX / Open Source) for secure knowledge retrieval and GenAI chatbot experiences.

● Built embedding and vector indexing pipelines, integrated RAG workflows, and optimized model latency, accuracy, and hallucination control through systematic evaluation.

Statistical Analysis Consultant Indium Software Chennai, India (Hybrid) June 2019 – Aug 2022

● Delivered end-to-end statistical analysis and machine learning solutions across Telecom, FinTech, Retail, Healthcare, HR, and E-commerce sectors—transforming complex data into actionable business insights and measurable impact.

● Customer Churn Prediction (Telecom/SaaS): Developed Logistic Regression and Random Forest models (AUC = 0.78) with churn-risk segmentation, achieving a 12% reduction in customer attrition and improving overall retention KPIs.

● Fraud Detection (Banking/FinTech): Built anomaly-detection frameworks using Z-score, IQR, and DBSCAN, delivering 92% fraud identification precision and reducing financial loss by 18%.

● A/B Testing & Experimentation (E-commerce): Designed and analyzed large-scale experiments using T-test, Z-test, and Bayesian inference, uncovering a 7.8% uplift in conversion rate and driving a global product rollout.

● Demand Forecasting (Retail/Supply Chain): Engineered ARIMA/SARIMA models with 87% accuracy, optimizing inventory management and reducing overstock by 14% across multiple store locations.

● Pricing Optimization (E-commerce): Conducted price elasticity modeling and regression analysis to simulate pricing scenarios, resulting in 11% revenue growth and improved profit margins.

● Healthcare Readmission Prediction: Applied Logistic Regression and Cox Proportional Hazards models to predict 30-day patient readmissions, improving early risk detection by 22% and supporting better care allocation.

● HR Attrition Prediction (People Analytics): Designed predictive models using Decision Trees and Logistic Regression, identifying key attrition drivers and enabling retention strategies that reduced turnover by 9%.

● Credit Scoring (Banking/FinTech): Developed WOE/IV-based logistic regression scorecards validated through KS, ROC, and PSI metrics, lowering default rates by 6% and enhancing credit risk assessments.

● Partnered with cross-functional stakeholders to translate statistical outcomes into data-driven business strategies, improving decision-making, profitability, and customer satisfaction across client portfolios. EDUCATION

Franklin University – Columbus, Ohio

Master of Science in Business Analytics January 2025 PROJECTS

Procurement Analytics & Supplier Performance Optimization

● Designed and implemented a centralized supplier performance dashboard using SQL, Excel, and Tableau, improving vendor visibility and enabling data-driven sourcing decisions.

● Automated procurement spend reports with Excel VBA, reducing manual effort by 25% and improving reporting accuracy across cross-functional teams.

● Conducted supplier benchmarking and category spend analysis, achieving a 15% reduction in raw material procurement costs through strategic sourcing.

● Optimized SAP-based purchase requisition workflows, increasing PO processing speed by 20% and improving compliance with procurement SLAs.

CERTIFICATIONS

● Certified in Planning and Inventory Management (CPIM)

● Lean Six Sigma Green Belt

● Tableau Data Analyst Certification

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