Data Analyst Integration

Vinaya Sunitha

************@*****.*** +1-309-***-****

PROFESSIONAL SUMMARY

Data Analyst with 5+ years of experience supporting large-scale data integration and reporting initiatives for healthcare and life sciences clients. Core expertise includes advanced PL/SQL development, Oracle Exadata and 10g environments, and automation of data validation and mapping processes. Proficient in designing and optimizing queries, building stored procedures, and creating automated data workflows to streamline compliance and regulatory reporting tasks. Skilled in utilizing Microsoft Excel, PowerPoint, and Oracle SQL Developer to deliver actionable insights and support business decision-making. Experienced in Agile team settings, contributing to requirement definition, test scenario design, sprint planning, and effort estimation. Recognized for analytical thinking, clear communication with both technical and business stakeholders, and the ability to manage multiple priorities in fast-paced environments.

EDUCATION

Masters in Computer Science

Western Illinois University

TECHNICAL SKILLS

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

Agile & Testing Tools: Agile (Scrum), Test Scenario Design, Effort Estimation Tools, Sprint Planning Tools

Data Integration & ETL: Data Mapping (Oracle), Data Validation (PL/SQL), Automated Data Workflows (Oracle Exadata)

Query & Analysis Tools: Microsoft Excel, Microsoft PowerPoint, Oracle SQL Developer, Advanced Querying (PL/SQL)

Programming & Scripting: Python, Stored Procedures (PL/SQL)

Compliance & Financial Systems: KYC Automation Tools, Wholesale Credit Products Platforms, Client Onboarding Solutions, Regulatory Reporting Tools

WORK EXPERIENCE

UnitedHealth Group, Data Analyst Nov 2023 - Present

●Developed and maintained complex PL/SQL queries and stored procedures to process large healthcare datasets, supporting analytics that improved patient outcomes and operational decision-making.

●Designed data integration workflows using Oracle Exadata to consolidate healthcare information from multiple sources, ensuring high performance and data consistency across the enterprise.

●Built automated data validation checks using SQL and Python, catching inconsistencies early and supporting accurate reporting for regulatory and compliance requirements.

●Created and refined data mapping logic to transform and standardize patient records, making it easier for downstream analytics teams to extract meaningful insights.

●Supported agile team activities by breaking down data requirements, estimating effort for new features, and participating in sprint planning sessions to prioritize key deliverables.

●Utilized Microsoft Excel and PowerPoint to summarize complex data findings for both technical teams and business stakeholders, helping drive clear and actionable decision-making.

●Tested new data integration solutions and collaborated with QA teams to ensure smooth deployment and minimal disruption to existing healthcare operations.

●Documented data models and process flows, making it easier for new team members and business users to understand the structure and flow of healthcare data.

●Regularly communicated technical solutions and project updates to both technical colleagues and non-technical leadership, adapting language and detail to fit the audience.

●Contributed to the design and review of secure data access policies, working closely with compliance teams to uphold HIPAA and internal data privacy standards.

Johnson & Johnson, Data Engineer May 2022 - Oct 2023

●Developed and optimized PL/SQL queries to support data analysis for wholesale credit products, ensuring data accuracy and consistency across multiple financial platforms in a regulated enterprise environment.

●Created and maintained Oracle Exadata stored procedures to automate client onboarding and KYC data validation, reducing manual processing time and supporting compliance with evolving regulatory standards.

●Designed test scenarios for end-to-end integration of new credit analytics modules, working with application teams to verify robust interfaces and seamless system performance under various conditions.

●Utilized Microsoft Excel and PowerPoint for preparing detailed analysis reports and executive summaries, tailoring presentations to both technical stakeholders and business leadership for improved decision-making.

●Defined business and technical requirements for enhancements to internal risk management systems, collaborating with cross-functional teams to clarify acceptance criteria and prioritize user stories in Agile sprints.

●Built data mapping solutions to integrate legacy credit systems with new onboarding workflows, ensuring data integrity and supporting accurate reporting for operational audit trails.

●Guided team members in estimating work and effort for new features, using agile methodologies to assign resources and track progress across multiple concurrent projects within the finance data domain.

●Analyzed cross-application data flows to identify gaps and opportunities for automation, connecting business processes from client onboarding through to credit risk assessment for greater operational transparency.

●Supported development of proof-of-concept data models for new credit risk analytics, applying innovative thinking to address data quality and integration challenges unique to the financial services context.

●Participated in regular scrum meetings, proactively identifying blockers and seeking input from subject matter experts to resolve complex issues in data transformation and regulatory compliance initiatives.

Delasoft, Data Engineer Jan 2019 - Nov 2021

●Built ETL pipelines using Azure Data Factory and PySpark to process and transform raw data into curated data zones in Azure

●Engineered secure API integrations via Azure API Management to ingest third-party partner data efficiently

●Applied RBAC and dynamic data masking policies in Snowflake to enforce data privacy and compliance

●Developed Python-based orchestration and monitoring frameworks for better governance of ETL jobs

●Partnered with BI teams to design performant data marts optimized for Power BI and custom analytics

●Created reusable pipeline templates for quick integration of new data sources

●Implemented monitoring dashboards using Azure Monitor for visibility into ETL operations

●Used Azure Repos and Pipelines to automate deployments and maintain pipeline consistency

●Led knowledge transfer and mentoring sessions to share engineering best practices with peers

●Assisted in modernizing legacy data workflows by adopting cloud-native technologies and architectures

CERTIFICATIONS

Licensed Academy Accreditation - Generative AI Fundamentals - DATABRICKS - April 2025 - April 2027

Foundations of AI and Machine Learning, MICROSOFT- Credential ID: DCH02XZBE1U6

Microsoft Azure Fundamentals: Generative AI - MICROSOFT

Azure AI Fundamental AZ AI -900

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