Data Analyst Integration

SIVA SAI KRISHNA TANINKI

Chicago IL US **********@*****.*** +1-312-***-****

PROFESSIONAL SUMMARY

Data Analyst with 4+ years of experience specializing in data integration, analysis, and reporting for enterprise clients. Skilled in designing and optimizing data pipelines using PL/SQL, Oracle 10g, and Oracle Exadata, with a strong command of SQL for complex data queries and stored procedure development. Proficient in ETL development leveraging Python, Spark, Databricks, and Delta Lake to support end-to-end data workflows. Well-versed in Microsoft Office Suite for documentation and reporting, and experienced in Agile environments, supporting sprint planning and backlog prioritization. Recognized for precise data validation, effective communication with both technical and business stakeholders, and the ability to manage multiple priorities in dynamic project settings.

TECHNICAL SKILLS

Databases: Oracle 10g, Oracle Exadata, PL/SQL, SQL

Testing & Validation: Unit Testing, User Acceptance Testing, Data Validation Frameworks

Agile & Project Tools: Agile (Scrum), Sprint Planning, Backlog Prioritization

Programming Languages: Python

Data Integration & ETL: ETL Pipelines (Python & SQL), Databricks, Spark, Delta Lake, External APIs, CI/CD Workflows

Office & Reporting Tools: Microsoft Excel, Microsoft Word, Microsoft PowerPoint, Microsoft Office Suite

WORK EXPERIENCE

MaintainX, Data Analyst Jan 2024 - Present

●Developed and fine-tuned complex PL/SQL queries and stored procedures within Oracle 10g environments to support maintenance operations data analysis and reporting for industrial teams.

●Built automated ETL pipelines using Python and SQL to ingest data from IoT-enabled assets, work orders, and external APIs, improving the quality and reliability of analytics-ready datasets.

●Created data models that transformed raw operational data into structured datasets supporting real-time analytics and machine learning initiatives across asset management and frontline workflows.

●Tested and validated data integration solutions to ensure seamless flow of information between maintenance systems and business applications, using unit tests and automated CI/CD workflows.

●Improved dashboarding and reporting capabilities by designing Excel-based tools and integrating results with Microsoft Office suite for easy consumption by both technical and non-technical users.

●Documented and maintained data dictionaries and technical specifications, ensuring clarity and consistency for analytics, software development, and compliance teams.

●Supported Agile project teams by estimating data-related tasks, breaking down requirements into actionable stories, and participating in sprint planning and backlog prioritization.

●Investigated data issues and performed root cause analysis to resolve inconsistencies, applying analytical thinking and problem-solving skills to support ongoing data quality improvements.

●Facilitated cross-functional communication by presenting insights and technical findings to both engineering teams and business stakeholders, tailoring messaging for each audience.

●Contributed to the development and improvement of a Databricks-based data platform, optimizing Spark and Delta Lake pipelines for large-scale batch and streaming workflows in a rapidly evolving environment.

DoseSpot, Data Engineer Jun 2021 - Jun 2023

●Developed PL/SQL queries and stored procedures in Oracle Exadata to support data analysis for healthcare transactions, focusing on compliance with client onboarding and KYC requirements.

●Created data validation frameworks using Oracle 10g to ensure integrity of patient and prescriber information during client onboarding and ongoing KYC review processes.

●Built Excel-based tools and automated reporting templates to track wholesale credit product performance, utilizing advanced Microsoft Office suite functions for healthcare analytics teams.

●Designed test scenarios and performed user acceptance testing for new data integration workflows, confirming robust, well-tested interfaces between pharmacy systems and DoseSpot applications.

●Contributed to Agile story refinement by defining healthcare data requirements and guiding estimation of analytics development tasks from conception through delivery lifecycle.

●Analyzed data flows across e-prescribing, client onboarding, and compliance modules to provide end-to-end mapping and identify process optimization opportunities for regulatory reporting.

●Developed and presented technical findings to both engineers and non-technical business users, tailoring communication style to ensure clarity and actionable insights in healthcare settings.

●Utilized analytical thinking and attention to detail to identify root causes of data inconsistencies in KYC checks, implementing solutions that improved data quality and regulatory readiness.

●Participated in Agile sprint planning and prioritized analytics deliverables for multiple concurrent projects, balancing business deadlines with data quality and compliance needs.

●Estimated effort and resources for data analytics initiatives, supporting financial planning and ensuring alignment with DoseSpot's business priorities and healthcare regulatory requirements.

EDUCATION

Master of Science, Business Analytics

Lewis University

PROJECTS

Predicting Auto Insurance Claims

Analyzed 54,000 records from U.S. Auto Insurance data with 48 features using Python and SQL.

Engineered features and handled data preprocessing using Pandas, NumPy, and Scikit-learn.

Trained and compared models: Logistic Regression, Decision Tree, Random Forest, and XGBoost.

Optimized model performance (XGBoost: F1-score 0.665, recall 39.2%) to identify high-risk customers.

Built automated data pipeline for ETL and deployed evaluation dashboards in Power BI.

Depression Prediction using NSDUH Survey Data

Conducted exploratory data analysis (EDA) and statistical testing to study mental health patterns.

Processed large-scale survey data using Python and visualized insights with Seaborn and Plotly.

Implemented XGBoost classifier with hyperparameter tuning for accurate prediction.

Achieved 70% accuracy and high sensitivity, aiding in early detection of depression risks.

Skills: Python, SQL, XGBoost, Scikit-learn, Power BI, Data Cleaning, Feature Engineering, ETL, EDA, Git, Model Evaluation

CERTIFICATIONS

Alation Data Governance Advocate - Alation

Tableau A–Z: Hands-On Tableau Training for Data Science - Udemy

SQL - HackerRank

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