Data Analyst Analysis

Venkata Vigna Pavan Reddy Bondu

Senior Data Analyst

Email: *************@*****.*** Ph No: 913-***-****

LinkedIn: linkedin.com/in/pavan-Reddy-bondu-

PROFESSIONAL SUMMARY:

9+ years of experience in IT and comprehensive industry knowledge as a Data Analyst on Data Analysis, Data Manipulation, Data Mining, Data Visualization and Business Intelligence.

Strong experience in Data Analysis, Data Profiling, Data Migration, Data Conversion, Data Quality, Data Integration, Metadata Management Services, and Configuration Management.

Proficient in reading, reviewing, and understanding XML output for accurate data interpretation and integration.

Extensively used Informatica PowerCenter and IDQ as ETL tools for extracting, transforming, loading, and cleansing data from various source data inputs to various targets, in batch and real-time.

Proven ability to optimize performance and reduce costs with AWS CloudWatch and AWS Cost Explorer.

Expert in leveraging AWS services, Redshift, S3, and Glue for efficient data storage, processing, and analysis.

Proficient in designing and managing AWS data pipelines, ensuring seamless integration of diverse data sources.

Good knowledge of SAS Macros, SAS SQL, SAS Stat, and SAS Graph in a UNIX environment.

Expertise in MS SQL Server suite of products SSRS, SSIS, and SSAS.

Extensive experience in the strategic development of a Data Warehouse and in performing Data Analysis and Data Mapping from an Operational Data Store to an Enterprise Data Warehouse.

Expertise in Data Modeling concepts, including Star Schema Modeling, Snowflake Schema Modeling, Fact, and Dimension tables.

Utilized web analytics tools to monitor and analyze website performance, providing actionable insights to improve overall user experience

Applied strong background in mathematics to design predictive models for customer behavior

Expert in data analysis and visualization using Tableau, Power BI, and Excel, with advanced proficiency in creating insightful reports and dashboards.

Developed and implemented complex data models using scripting languages, improving the accuracy of predictive analytics

Skilled in Python and SQL programming for data manipulation, automation, and scripting, with experience in Java for cross-functional development.

Proficient in big data technologies including Hadoop and Apache Spark, enabling scalable data processing and analytics.

Excelled at leveraging a variety of analytics tools to design and implement data-driven solutions that improved operational efficiency.

Excelled at analyzing data to support strategic business decisions, resulting in increased company profitability

Expert in data visualization and reporting with Tableau, Power BI, and Google Analytics.

Proficient in SQL Server, PostgreSQL, MySQL, Oracle, Redshift, and Snowflake for robust database management.

Experienced in utilizing Hadoop ecosystem tools including HDFS, Hive, Pig, and Spark for big data processing.

Adept at creating and managing SQL-based workflows and data pipelines for efficient data handling.

Proficient in using Jupyter Notebook for interactive data analysis and visualization.

Experienced with ETL tools, including Apache Airflow, Informatica, and DataStage, to ensure efficient data integration and transformation processes.

Proficient in cloud platforms, including Azure services, Data Lake, Databricks, and SQL Data Warehouse, as well as AWS offerings, Redshift and S3, for scalable data storage and processing.

Strong background in database systems including MS SQL Server, Oracle, Teradata, SAP HANA, and Snowflake, providing comprehensive data management solutions.

Skilled in data warehousing and OLAP methodologies with hands-on experience in data modeling using Erwin and Embarcadero.

Experienced in using Apache Kafka for real-time data streaming and integration, enhancing data flow and system performance.

Skilled in utilizing Jupyter Notebook, RapidMiner, and Google Analytics for advanced data analysis and reporting.

Well-versed in SSIS, SSRS, SSAS, and Power Pivot, with a solid understanding of DAX, UML, and Rational Rose for effective data management and visualization.

Proficient in Python, R, SQL, and SAS for advanced data analysis and statistical modeling.

Experienced in leveraging Azure Synapse Analytics and AWS Glue for scalable data integration and processing.

Skilled in designing and implementing ETL processes using Azure Data Factory and AWS S3.

Experienced in advanced Excel functions, including Pivot Tables, VBA, and Macros for data manipulation.

Exposure to implementation and operations of data governance, data strategy, data management, and solutions.

Created and managed Azure Machine Learning models for predictive analytics and data-driven decision-making.

Experience in SQL, DML, and DDL, writing complex SQL queries and testing scripts for data validation against relational databases, including Data Warehouse systems.

TECHNICAL SKILLS:

Programming & Scripting

Python, SQL, R

ETL & Data Integration

Informatica PowerCenter, Apache Airflow, DataStage, Azure Data Factory, AWS Glue, SSIS

Big Data Technologies

Hadoop, Apache Spark, Hive, Pig, MapReduce, Databricks, HDFS

Cloud Platforms

AWS, Azure,

Database Management

MS SQL Server, PostgreSQL, MySQL, Oracle, Snowflake, SAP HANA, Teradata, SQL Server Management Studio, Oracle Data Guard

Data Warehousing

Data Warehouse development, Star-Schema, Snowflake Schema, Erwin, Embarcadero, OLAP

DataAnalysis& Visualization

Tableau, Power BI, Excel, Google Analytics, Python, R, SAS, SaaS, Jupyter Notebook

Reporting Tools

SSRS, Power Pivot, RapidMiner, Tableau

Machine Learning

Scikit-learn, TensorFlow, IBM SPSS, Azure Machine Learning

Data Modeling

ER Diagrams, Data Modeling, Dimensional Modelling

Data Management

Data Governance, Data Strategy, Data Quality, Metadata Management Services, Configuration Management

Real-time Data Processing

Apache Kafka, AWS Kinesis

Data Pipelines

Azure Data Factory, AWS Glue, Apache Airflow, DataStage, Informatica

DataCleaning& Transformation

Alteryx, Python, SAS, RapidMiner

VersionControl& Collaboration

Jira, Confluence,

PROFESSIONAL EXPERIENCE:

Client: New Jersey Department of Agriculture, Trenton, NJ. Mar 2022 - Present

Role: Sr. Data Analyst

Responsibilities:

Performed in team responsible for the analysis of business requirements and design implementation of the business solution.

Analyzed database requirements from the users in terms of loading dimensions and fact tables using SSIS Packages and worked extensively in data analysis by querying in SQL and generating various PL/SQL objects.

Developed ETL processes using Azure Data Factory to integrate and transform data from diverse sources into a centralized data warehouse.

Leveraged Python libraries, Pandas and NumPy for data manipulation and analysis, improving the accuracy and efficiency of data-driven insights.

Developed and maintained Azure Data Factory pipelines for data integration and ETL processes, optimizing data flow and processing efficiency.

Designed and implemented data storage solutions using Azure SQL Database and Azure Data Lake Storage, ensuring scalability and performance.

Developed advanced algorithms to analyze telemetry data, providing key insights that drove operational efficiency

Implemented machine learning models with Scikit-learn to predict trends and patterns.

Executed complex SQL queries and managed databases, including PostgreSQL, MySQL, and Oracle, to extract, clean, and analyze large datasets for comprehensive reporting.

Developed ETL processes using Informatica and DataStage to streamline data extraction, transformation, and loading workflows.

Implemented data integration solutions with Apache Airflow for efficient workflow orchestration and automation.

Designed and maintained data pipelines with Apache Spark and Hadoop to handle large-scale data processing and generated comprehensive analytical reports by running SQL queries against current databases to conduct data analysis.

Utilized Python and SQL for data analysis, data cleaning and generating actionable insights from complex datasets.

Created interactive dashboards and reports in Tableau to visualize key metrics and business trends.

Leveraged Snowflake and Oracle databases for data storage, querying, and optimization.

Developed and maintained data models and ER diagrams to support database design and data architecture.

Performed statistical analysis and predictive modeling using IBM SPSS and RapidMiner to support data-driven decision-making.

Utilized SaaS platforms for data extraction, cleaning, and manipulation to aid in critical decision-making

Conducted data analysis and visualization tasks in Jupyter Notebook to explore data patterns and trends.

Analyzed web traffic and user behavior with Google Analytics to optimize marketing strategies and improve user engagement.

Created interactive dashboards and reports in Tableau and Excel, leveraging VBA for automation and advanced analytics to support strategic decision-making.

Applied statistical analysis techniques using R and SAS to uncover insights and drive data-driven decisions.

Analyzed web and user behavior data with Google Analytics to optimize marketing strategies and enhance user experience based on detailed reporting and analysis.

Implemented AI algorithms to interpret complex data sets, resulting in the optimization of business operations.

Reviewed extensive SQL Queries with complex multi-table joins and nested queries.

Environment: SQL, PL/SQL, SSIS, Azure Data Factory, Python, Azure SQL Database, Azure Data Lake Storage, Scikit-learn, PostgreSQL, MySQL, Oracle, Informatica, Apache Airflow, Apache Spark, Hadoop, Tableau, Snowflake, IBM SPSS, RapidMiner, Jupyter Notebook, Google Analytics, Excel, R, SAS, SaaS.

Client: Wells Fargo, San Francisco, California. Oct 2019 – Feb 2022

Role: Data Analyst

Responsibilities:

Developed and maintained ETL pipelines using AWS S3 and Snowflake for efficient data processing and storage.

Implemented API Gateway to manage and secure RESTful APIs, integrating with AWS Lambda for serverless.

Utilized CloudWatch for monitoring and logging of AWS Lambda functions.

Designed and managed interactive dashboards leveraging SQL and Python for data analysis and visualization.

Performed complex data analysis using Hadoop, Hive, Pig, and MapReduce.

Developed and maintained ETL pipelines using Python and Spark to process and analyze large datasets.

Utilized AWS services to design scalable data solutions and manage cloud-based data storage and processing.

Created and optimized SQL queries for data extraction and analysis from SQL Server, Oracle, and SAP HANA.

Leveraged Databricks for distributed data processing and machine learning model development in a cloud environment.

Conducted advanced data analysis and visualization using Tableau and Google Analytics to drive actionable insights and Worked on Performance Tuning and understanding Joins and Data distribution.

Designed and implemented data pipelines using AWS services, Glue, Lambda, and S3 for scalable ETL processes.

Implemented data cleaning and transformation techniques with Alteryx, SAS, and RapidMiner to prepare data for analysis.

Utilized advanced analytics to optimize Customer Service Operations, resulting in significant cost savings

Developed statistical models and performed predictive analytics using IBM SPSS and Python libraries.

Collaborated with cross-functional teams to document data workflows and requirements in Jira and Confluence.

Analyzed and interpreted complex data sets to identify trends, patterns, and anomalies.

Created and maintained Jupyter Notebooks for data exploration, visualization, and reporting, ensuring reproducibility and transparency.

Built and optimized machine learning models with Python, employing libraries Scikit-Learn and TensorFlow for predictive analytics.

Executed data extraction and reporting using SQL, PostgreSQL, MySQL, and Oracle Enterprise Manager for cross-platform data integration.

Leveraged Matplotlib and Seaborn for creating detailed visualizations and statistical plots.

Managed AWS infrastructure, including EC2 instances, EBS volumes, IAM roles, and Route 53 for scalable and secure data solutions.

Written complex T- SQL, SQL queries using joins, sub queries and correlated sub queries.

Worked on Data Verifications and Validations to evaluate the data generated according to the requirements is appropriate and consistent.

Created multiple automated reports and dashboards sourced from data warehouse using Tableau.

Designed and developed PL/SQL stored procedures to increase the performance of system.

Environment: SQL, AWS S3, Snowflake, API Gateway, AWS Lambda, CloudWatch, Python, Hadoop, Hive, Pig, MapReduce, Spark, SQL Server, Oracle, SAP HANA, Databricks, Tableau, Google Analytics, AWS Glue, Alteryx, SAS, RapidMiner, IBM SPSS, Jupyter Notebooks, PostgreSQL, MySQL, Matplotlib, Seaborn.

Client: Max Life Insurance Company Limited, Gurgaon, India. Jun 2017 – Aug 2019

Role: Data Analyst

Responsibilities:

Performed source data analysis, data discovery, data profiling, and data mapping.

Developed SSRS Reports as well as Drill through Reports, drill-down Reports, linked reports, and parameterized reports.

Designed and deployed scalable data pipelines using Azure Data Factory for ETL processes.

Optimized data storage and retrieval with Azure SQL Database and Azure Synapse Analytics.

Implemented data warehousing solutions utilizing Azure Data Lake for large-scale data storage.

Created interactive dashboards and visualizations in PowerBI to present insights from SQL, MySQL, and PostgreSQL databases.

Utilized SQL and Excel to analyze and report on underwriting data, identifying key trends and recommending improvements to streamline processes.

Designed and executed complex statistical analyses using IBM SPSS to uncover trends and insights from large datasets.

Developed and maintained technical documentation, including underwriting guidelines and process flows, to support system functionality and user understanding.

Led testing efforts by creating test cases and scenarios, validating data output, and ensuring seamless integration with existing systems.

Managed complex research projects for the enhancement of data analysis techniques and methodologies

Interacted directly with clients and stakeholders, addressing inquiries, clarifying requirements, and supporting system enhancements.

integrated results with Google Analytics and Oracle Data Guard for comprehensive reporting.

Identified, analyzed, and documented defects, errors, and inconsistencies in the application using MS Excel.

Utilized Python libraries, Pandas, NumPy, and Scikit-learn to perform data cleaning, transformation, and predictive modeling, driving actionable insights.

Conducted advanced statistical analysis and data visualization using R and SAS, producing comprehensive reports and dashboards in PowerBi and Excel.

Developed and maintained data pipelines in Jupyter Notebooks for exploratory data analysis and reporting.

Implemented and maintained data pipelines using Hadoop for efficient processing and storage of big data, ensuring high-quality data management practices.

Leveraged Google Analytics to track and analyze web traffic, providing insights into user behavior and supporting data-driven decision-making for marketing strategies.

Developed UNIX Shell scripts to automate various periodically repetitive database processes.

Designed and developed Ad-hoc reports as per business analyst, operation analyst, and project manager data requests.

Collaborated with cross-functional teams to gather business requirements, translating them into technical specifications and actionable insights for decision-making.

Environment: SSRS, Azure Data Factory, Azure SQL Database, Azure Synapse Analytics, Azure Data Lake, PowerBI, IBM SPSS, Google Analytics, Oracle, Python, R, SAS, Jupyter Notebooks, Hadoop, SQL, MySQL, PostgreSQL.

Client: Fortis Healthcare, Gurgaon, India. Jul 2015 – May 2017

Role: Data Analyst

Responsibilities:

Developed and maintained scalable data pipelines using AWS EC2 instances and Hadoop for large-scale data processing.

Implemented and managed IAM roles and policies to ensure secure access control across AWS resources.

Utilized Python and Jupyter Notebooks for data analysis, visualization, and reporting.

Developed and optimized ETL processes using AWS services, SSIS, and Python to streamline data integration and ensure efficient data workflows.

Built complex data models and reports in PowerBI using DAX and MS Excel to provide actionable insights.

Utilized SQL to perform advanced data querying, analysis, and reporting.

Conducted data analysis and statistical modeling with SAS to identify trends and patterns, supporting strategic planning and business performance evaluations.

Implemented automated data pipelines and reporting solutions, leveraging Python and AWS to enhance data accuracy and reduce manual processing time.

Conducted advanced data analysis and statistical modeling with R.

Environment: AWS EC2, Hadoop, IAM, Python, Jupyter Notebooks, SSIS, PowerBI, DAX, MS Excel, SQL, SAS, R.

CERTIFICATION: Microsoft Certified: Power BI Data Analyst Associate

EDUCATION: Jawaharlal Nehru Technology University, Hyderabad, TS, India

BTech in Computer Science and Engineering, June 2011 - May 2015

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