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Click here or scroll down to respond to this candidate Candidate's Name
PHONE NUMBER AVAILABLEEMAIL AVAILABLE SENIOR DATA ANALYST
PROFESSIONAL SUMMARY: Experienced Senior Data Analyst with over 9+ years of expertise in PostgreSQL, SQL, Microsoft Excel, QlikView, and Apache Hadoop. Proven track record of implementing efficient data-driven solutions utilizing Spark, GIT, Informatica, Power BI, and various visualization tools. Expertise in designing, deploying, and managing effective reporting and dashboarding solutions to improve decision-making processes across industries. Highly skilled in data documentation, creating detailed reports and analytics to guide business strategies and implementation efforts. Demonstrated ability to manage large datasets, applying complex data analysis and visualization techniques to generate actionable business insights. Proficient in version control using GIT, enhancing collaborative project management and maintaining code integrity across data initiatives. Strong background in comprehensive documentation practices, ensuring clarity and consistency in reporting findings and recommendations. Leveraged SQL, SSIS, Oracle Data Integrator, and Apache NiFi to enhance data flow and system integrations effectively. Specialized in data cleansing and transformation to support comprehensive business intelligence and analytics platforms. Developed and managed data exchanges via FTP/SFTP, integrating multiple systems and databases using RESTful APIs efficiently. Utilized extensive knowledge of Linux to enhance system performance and interoperability across various data platforms. Further advanced my career as a Data Mining Specialist, focusing on retail analytics and machine learning applications. Applied Python, TensorFlow, and PyTorch extensively to develop predictive models that enhance retail operations and customer engagement. Utilized Microsoft Azure, including Azure ML and Azure Databricks, to deploy scalable and efficient cloud-based data solutions. Employed Agile and Scrum methodologies rigorously to manage and deliver complex data projects on time and within budget. At Delta Airlines, I spearheaded competitive analysis and market research initiatives using SPSS and Qualtrics to identify growth opportunities. Integrated CRM with Adobe Analytics to refine data-driven marketing strategies, enhancing customer engagement and retention. Expert in AWS QuickSight and AWS S3, implementing robust data storage and visualization solutions to support business intelligence efforts. Currently, at Highmark HealthCare, leading healthcare data analysis projects that utilize advanced analytics and machine learning to improve patient care. Employ SQL, SharePoint, and Confluence to manage data effectively, enhancing team collaboration and project documentation. Expert in deploying Tableau for creating insightful and interactive dashboards that illustrate complex data relationships in the healthcare sector. Implement AWS technologies, including Amazon SageMaker and AWS Redshift, to deliver robust and scalable data solutions in a healthcare setting. Drive data automation initiatives using Alteryx, enhancing efficiency and accuracy in data processing and analytical workflows. Apply my expertise in R language to conduct advanced statistical analysis, providing deeper insights into healthcare data trends and patterns.TECHNICAL SKILLS:Skill CategoryTechnologies/ToolsDatabase ManagementPostgreSQL, Oracle, Microsoft SQLData Analysis and ReportingSQL, Microsoft Excel, SPSS, Power BI, TableauData IntegrationInformatica, SSIS, Oracle Data Integrator, Apache NiFi, KafkaProgramming LanguagesPython, MATLAB, RMachine Learning and AITensorFlow, PyTorch, Amazon SageMaker, Azure MLData VisualizationQlikView, Power BI, Tableau, Looker, AWS QuickSightCloud PlatformsAWS S3, AWS Cloud, AWS Redshift, Microsoft AzureVersion ControlGITProject ManagementAgile, Scrum
PROFESSIONAL EXPERIENCE:Client: Highmark HealthCare, Camp Hill, PA Jul 2023 to till dateRole: Senior Data AnalystRoles & Responsibilities:
Analyzed healthcare data trends using SQL to identify patterns that improved patient care and operational efficiency. Developed SQL queries that extracted insights from healthcare data, supporting strategic decisions that enhanced facility operations. Utilized Microsoft Excel to create reports that summarized patient outcomes, facilitating quick access and administrative review. Designed SharePoint workflows for document management, which improved team collaboration and data accessibility across departments. Authored detailed documentation on healthcare data processes, enhancing understanding and ensuring compliance with regulatory standards. Configured Tableau dashboards to visualize complex patient data, supporting proactive healthcare measures and planning. Integrated advanced analytics to predict healthcare trends, enhancing the quality and effectiveness of patient care. Employed Amazon SageMaker to build and train machine learning models that accurately predicted patient outcomes and resource needs. Managed AWS S3 data storage solutions, ensuring secure and scalable data access for healthcare analysis. Implemented AWS Cloud technologies to streamline data processing and accessibility, enhancing real-time data analysis capabilities. Developed predictive models using Apache Spark ALS, which optimized resource allocation and patient care strategies. Streamlined data warehousing using AWS Redshift, improving the efficiency of data aggregation and retrieval processes. Automated routine data tasks with Alteryx, increasing process efficiency and reducing potential for human error. Enhanced data recognition and processing using AWS Recognition, improving the accuracy of patient data management. Conducted advanced statistical analysis using the R language, deriving deeper insights into healthcare trends and patient needs. Utilized Confluence to manage project documentation, ensuring that all data processes were well-documented and accessible. Integrated Tableau in reporting workflows, providing decision-makers with interactive tools for better data interpretation. Leveraged AWS cloud services to ensure robust data backup and recovery processes, securing critical healthcare data. Developed comprehensive SharePoint sites that centralized healthcare documentation, enhancing data governance and compliance. Created advanced analytics models in Amazon SageMaker, which supported the development of personalized patient care plans. Executed SQL-based data cleansing processes in PostgreSQL, ensuring high data quality and reliability for analysis. Utilized Excel pivot tables to summarize research findings, enabling healthcare staff to quickly assess data insights. Configured AWS QuickSight dashboards that provided executives with real-time insights into operational performance. Employed AWS S3 for efficient data archiving, ensuring long-term accessibility and compliance with healthcare regulations. Documented all data analytics processes and findings in detailed reports, providing a basis for ongoing healthcare strategy development.Environment: AWS SageMaker, Tableau, Alteryx, AWS Redshift, Apache Spark, Quick Sight, R, AWS S3, AWS Recognition, Excel, Power BI, and SharePoint.Client: Delta Airlines, Atlanta, GA Apr 2021 to Jul 2023
Role: Data AnalystRoles & Responsibilities: Conducted competitive analysis using SQL to identify key trends and opportunities that informed strategic decisions in the aviation industry. Analyzed customer feedback data with SPSS to drive improvements in customer service and operational efficiency. Utilized Qualtrics for comprehensive survey data analysis, enhancing customer satisfaction tracking and response strategies. Developed Tableau visualizations to effectively report on market research findings, supporting strategic decision-making processes. Integrated CRM data with Adobe Analytics to refine marketing strategies and campaigns, increasing customer engagement and sales conversions. Managed Experian data integration to enhance customer profiling and targeting, improving the effectiveness of marketing campaigns. Utilized Looker for in-depth analytical reports, aiding executives and stakeholders in making informed strategic decisions. Designed ETL processes to integrate various source systems using Informatica, ensuring consistency and reliability of aviation data. Employed AWS QuickSight for agile data visualization and dashboarding, enhancing the speed of operational decision-making. Streamlined data management using Microsoft SQL to ensure robust data governance and security in aviation operations. Leveraged Python for advanced analytics projects, improving forecasting accuracy and operational planning. Documented all data processes and protocols to ensure compliance with aviation industry regulations and standards. Deployed AWS S3 for secure and scalable data storage, supporting critical enterprise data needs in the aviation sector. Enhanced competitive intelligence by analyzing industry trends with SQL and Tableau, facilitating proactive strategic adjustments. Optimized customer relationship management through the integration of CRM and Adobe Analytics, improving customer loyalty programs. Improved marketing ROI by leveraging Experian data integrations to execute targeted advertising campaigns effectively. Automated data reporting processes using Microsoft SQL and Tableau, reducing time and effort required for data preparation. Streamlined customer survey analysis by employing Qualtrics, which provided deeper insights into customer preferences and behaviors. Conducted rigorous data quality checks using Informatica, ensuring the accuracy and usability of operational data. Facilitated real-time data sharing across business units by implementing secure data transfer protocols with AWS S3. Developed comprehensive training materials on data handling and analysis protocols, enhancing team skills and data literacy. Managed cross-functional data integration projects that combined financial, operational, and customer data to support comprehensive analytics. Oversaw the development and maintenance of Looker dashboards that provided ongoing insights into key performance indicators and metrics.
Environment: Python, NumPy, pandas, TensorFlow, PyTorch, AWS Lambda, AWS S3, Tableau, Azure Machine Learning, Jupyter Notebook, Azure ML, MATLAB, AWS Antenna, SQL, R, Git, Excel, Power BI.Client: QVC, West Chester, PA Nov 2018 to Mar 2021Role: Data Mining Specialist Roles & Responsibilities: Developed Python scripts for comprehensive data analysis, enhancing insights into retail operations and customer behavior. Utilized Jupyter Notebook for iterative data exploration and visualization, improving data-driven decision-making in retail. Implemented TensorFlow models to accurately predict consumer buying patterns, enhancing stock management and marketing strategies. Applied PyTorch in deep learning projects to enhance product recommendation systems, improving customer experience and sales. Leveraged MATLAB for complex mathematical modeling, supporting inventory management and pricing strategies in retail. Utilized Microsoft Excel for financial reporting and trend analysis, aiding in budget preparation and fiscal decision-making. Employed Power BI to create dynamic retail performance dashboards, enhancing key performance indicator tracking and reporting. Integrated Microsoft Azure for cloud-based data storage and computation, ensuring scalability and flexibility in data handling. Documented analytical methodologies and results comprehensively, ensuring reproducibility and adherence to retail industry standards. Employed Scrum practices to effectively manage data projects, enhancing team agility and project delivery timelines. Configured Azure ML for developing machine learning projects, improving sales forecasting accuracy and customer segmentation. Utilized Azure Databricks for big data processing, enhancing data analysis capabilities and support for data scientists. Developed comprehensive reports for business use cases, facilitating strategic retail decisions and operational adjustments. Analyzed retail sales data using SQL, providing insights that led to optimized product placements and promotions. Created dashboards and reports in Power BI, visualizing sales trends and customer behavior for executive review. Conducted data cleansing and preparation using Python and MATLAB, ensuring data quality for analysis and reporting. Integrated TensorFlow and PyTorch models into retail analytics processes, predicting trends and customer preferences effectively. Automated routine reporting tasks with Jupyter Notebook and Python, increasing efficiency and accuracy in data presentation. Managed cloud-based data integrations and migrations to Microsoft Azure, ensuring data availability and disaster recovery. Led training sessions on data analytics tools and practices, enhancing the analytical skills of the retail team.
Environment: SQL, Looker, MATLAB, R, Azure Stream Analytics, Azure SQL, Microsoft Azure, Datawarehouse technologies, Matplotlib, Excel, Power BI, Data Studio, AWS S3, Informatica.Client: Nascent Info Technologies, India Jan 2017 to Aug 2018Role: Database AnalystRoles& Responsibilities:
Enhanced data integration using SQL, improving data exchange across diverse business systems and platforms. Designed and implemented ETL workflows with SSIS, streamlining data transformation processes for better business intelligence. Utilized Oracle Data Integrator for complex data integration tasks, ensuring high data quality and usability for analytics. Managed comprehensive data cleansing projects using Informatica, ensuring the accuracy and relevance of business intelligence data. Configured Apache NiFi for efficient data routing and transformation, optimizing data flows for enhanced decision-making. Implemented Kafka for real-time data streaming, supporting timely data availability and decision-making in business operations. Developed Excel-based reports for detailed operational analysis, facilitating quick management reviews and operational adjustments. Managed XML and JSON data formats for efficient data exchange and storage, enhancing system interoperability and performance. Utilized FTP/SFTP for secure data transfers between systems, enhancing data security and compliance with industry standards. Documented all data processes and technologies in detailed manuals, ensuring clarity and continuity in data management. Leveraged Oracle Data Integrator to automate complex data transformation tasks, reducing manual effort and increasing accuracy. Created dashboards and visualizations in Microsoft Excel, providing actionable insights into key business metrics. Executed data transformations using Apache NiFi, aligning data formats and schemas across multiple source systems. Implemented security protocols for data transfers using FTP/SFTP, ensuring compliance with data protection regulations. Utilized Kafka to manage data pipelines, ensuring efficient handling of large data streams in real-time. Conducted training sessions on SSIS and Informatica for the data team, improving their skills in data handling and processing. Streamlined data reporting processes using SSIS, enabling more efficient generation and distribution of business reports. Optimized data quality checks using Informatica, ensuring high standards of data integrity and reliability for business analysis.Environment: SQL, Power BI, SAP Business Objects, SSRS, MDX, DAX, GIT, Apache NiFi, Excel, XML & JSON, FTP/SFTP (Secure Data Transfers), ETL.Client: iGATE Global Solutions Limited, India Jun 2015 to Dec 2016Role: Data Analyst Roles & Responsibilities: Utilized PostgreSQL for robust database management, enhancing data storage, retrieval, and management efficiency. Developed complex SQL queries for in-depth data analysis, supporting diverse client needs and strategic business decisions. Created Excel-based dashboards for real-time data visualization, enhancing decision-making and operational monitoring. Implemented Apache Hadoop for effective big data processing, increasing the organization's data handling capabilities. Configured Spark for real-time data processing, improving data analysis speed and efficiency in large-scale projects. Managed version control with GIT, enhancing code management and collaboration across the data team. Developed Informatica workflows for efficient data integration, improving data availability and accuracy across business units. Utilized Power BI to create interactive and informative reports and dashboards, enhancing data-driven decision-making. Authored comprehensive documentation for data handling processes, ensuring regulatory compliance and operational transparency. Developed detailed reports to illustrate analytical findings, supporting strategic planning and business development efforts. Leveraged QlikView to develop advanced visualization tools, providing deeper insights into data trends and anomalies. Applied GIT for source control and version management, ensuring data integrity and collaborative development. Conducted data analyses using Apache Spark, extracting valuable insights from large datasets quickly and efficiently. Implemented data visualization techniques in Power BI, simplifying complex datasets for non-technical stakeholders. Enhanced data processing and analysis capabilities using Apache Hadoop, enabling the handling of big data projects effectively.Environment: PostgreSQL, SQL, QlikView, Apache Hadoop, Git, Informatica, Power BI, Microsoft Excel, Apache Spark, Power BI.Education: Bachelor of Technology (B.Tech) in Computer Science from JNTU, Hyderabad, Telangana, India. - 2016 |
