Data Analyst Analysis

Nagesh Katla

Data Analyst

Email: ***********@*****.***

Phone Number: +1-224-***-****

Summary:

• Over 6+ years of experience in data analysis, data modelling, and business intelligence across various industries, including finance, healthcare, and retail.

• Expertise in designing, developing, and optimizing data pipelines, ensuring efficient ETL processes to integrate data from multiple sources.

• Strong proficiency in data visualization tools like Tableau, Power BI, and Qlik Sense, creating interactive dashboards and reports for actionable insights.

• Skilled in advanced SQL programming for complex queries, including optimization, performance tuning, and troubleshooting.

• Proven ability to perform data cleaning, transformation, and enrichment to ensure data quality and consistency across all systems.

• In-depth knowledge of relational databases such as SQL Server, Oracle, MySQL, and non- relational databases like MongoDB and NoSQL.

• Strong analytical skills in interpreting large datasets, providing data-driven insights to senior management for strategic decision-making.

• Proficient in Python, R, and SQL for performing data analysis and statistical modeling, including regression analysis and predictive analytics.

• Experience with big data technologies like Hadoop, Spark, and Hive for processing large datasets in distributed computing environments.

• Collaborated with business stakeholders to gather requirements and translate them into technical solutions that meet business needs.

• Led and mentored junior data analysts, providing guidance on best practices for data analysis and ensuring high-quality deliverables.

• Expertise in designing and implementing key performance indicators (KPIs) to track and monitor business performance.

• Developed automated reporting processes, reducing manual effort and ensuring timely, consistent delivery of reports.

• Strong understanding of data governance, privacy regulations (e.g., GDPR, CCPA), and data security best practices.

• Experience with cloud platforms such as AWS and Azure, deploying data solutions and managing cloud-based data infrastructure.

• Worked cross-functionally with operations, planning, and IT teams to integrate HASTUS data with other enterprise systems (e.g., CAD/AVL, payroll, performance monitoring tools).

• Hands-on experience in machine learning algorithms (e.g., decision trees, clustering, and regression models) for predictive analytics and forecasting.

• Conducted exploratory data analysis (EDA) to identify trends, patterns, and correlations that inform business strategies.

• Worked on end-to-end implementation of data analytics solutions, from data collection and processing to final reporting and presentation.

• Designed and optimized data models for reporting and analytics, ensuring high performance and scalability.

• Experience with data integration tools such as Talend, Informatica, and SSIS for seamless ETL operations across platforms.

• Excellent communication and presentation skills, effectively translating complex technical data insights to non-technical stakeholders for decision-making. Technical Skills:

Data Analysis & Modeling: Python, R, SQL, regression analysis, predictive modeling Business Intelligence & Visualization: Tableau, Power BI, Qlik Sense Database Management: SQL Server, Oracle, MySQL, MongoDB, NoSQL Big Data Technologies: Hadoop, Spark, Hive

ETL & Data Integration: Talend, Informatica, SSIS, Apache NiFi Cloud Platforms: AWS, Azure

Machine Learning: Decision trees, regression models, clustering Data Quality & Transformation: Data cleaning, enrichment, validation Reporting & Automation: Automated report generation, KPI dashboards Data Governance & Security: GDPR, CCPA compliance, data security Exploratory Data Analysis (EDA): Identifying trends, outliers, and correlations Mentorship & Collaboration: Team leadership, project management Data Communication: Presenting insights to technical/non-technical audience Certifications:

• AWS Certified Developer

• AWS Data Analyst

• IBM Data Analyst

Employment History:

Data Analyst SAF Dynamic Solutions Remote TX, USA April 2025 – till date

• Led the design and implementation of Apache Spark and Hadoop-based real-time data processing systems, enabling large-scale analytics for multiple business units, reducing data processing time by 30%.

• Developed and implemented interactive Tableau dashboards to track key performance indicators (KPIs) across sales, marketing, and customer service, empowering senior management to make data-driven decisions in real-time.

• Managed the migration of on-premise data infrastructure to AWS and Azure cloud platforms, offering scalability and cost-effectiveness for data storage, processing, and analytics, improving efficiency by 25%.

• Implemented predictive models using TensorFlow and Keras, improving forecasting accuracy for sales and demand planning, resulting in a 15% enhancement in forecasting accuracy over previous models.

• Supported the implementation of new HASTUS modules or upgrades, contributing to user testing and validation processes.

• Trained end-users and stakeholders on HASTUS data interpretation and reporting, improving team proficiency and data literacy002E.

• Utilized HASTUS scheduling and planning modules to extract, analyze, and optimize transit schedules, improving route efficiency and on-time performance.

• Developed custom reports and dashboards using HASTUS data to support operational decision- making and long-term planning.

• Enhanced database performance by optimizing SQL Server and MongoDB queries, implementing efficient indexing strategies, and reducing query execution time by up to 40%.

• Led Salesforce data integration using SOQL queries, enabling enhanced reporting and analytics for the sales team, including lead conversion, customer lifetime value analysis, and churn predictions.

• Optimized ETL pipelines through automation with Python and SQL, simplifying data extraction, transformation, and loading (ETL) processes, reducing manual errors and streamlining workflows.

• Collaborated closely with business stakeholders to determine data requirements and translate them into actionable data models, mapping them to business objectives and improving overall reporting accuracy.

• Designed and maintained real-time data pipelines for live data streaming and processing using Apache Kafka, Spark Streaming, and AWS Lambda, enabling better decision-making through faster access to data.

• Mentored junior analysts on data analysis, HASTUS,visualization, and reporting best practices, fostering a high-performing and collaborative team culture and ensuring continuous skills development.

• Developed automated data validation and monitoring systems to ensure data quality and consistency, improving the reliability of reports and dashboards by identifying and correcting data anomalies in real-time.

• Contributed to the design of a comprehensive data governance strategy, ensuring compliance with industry standards, security protocols, and best practices across all data management processes.

• Collaborated with data engineers to design scalable data architectures that support growing business needs, contributing to the long-term success of the analytics team.

• Implemented advanced data visualization techniques such as heat maps, Pareto charts, and geo- visualizations, offering more comprehensive insights into key business metrics.

• Developed ad-hoc and scheduled reports for different departments, including finance, operations, and marketing, to ensure timely access to accurate data for decision-making. Environment: Tableau, Power BI, SQL Server, MongoDB, AWS, Azure, Apache Spark, Hadoop, TensorFlow, Keras, Python, SOQL, Salesforce, Apache Kafka, Data Warehousing, HASTUS, ETL processes, Machine Learning.

Database Analyst CUC Chicago, IL Sep 2022 - Jan 2025

• Directed the design and implementation of Hadoop-based and Apache Spark real-time data processing systems, supporting large-scale analytics across business units, reducing data processing time by 30%.

• Developed and implemented interactive Tableau dashboards to track key performance indicators (KPIs) in sales, marketing, and customer service, enabling senior management to make real-time data-driven decisions.

• Managed on-prem data infrastructure migration to AWS and Azure cloud environments, boosting scalability, cost-effectiveness, and efficiency for data storage, processing, and analysis by 25%.

• Built predictive models using TensorFlow and Keras, improving sales forecasting accuracy and demand planning, increasing the accuracy of previous models by 15%.

• Enhanced database performance by optimizing SQL Server and MongoDB queries, implementing effective indexing strategies, and reducing query execution times by 40% or more.

• Guided Salesforce data integration using SOQL queries, enabling improved reporting and analytics for the sales team, including lead conversion, customer lifetime value analysis, and churn forecasting.

• Automated ETL workflows with Python and SQL, simplifying data extraction, transformation, and loading (ETL) processes, reducing manual errors, and streamlining workflows.

• Worked closely with business stakeholders to understand data needs, converting them into actionable data models and aligning them with business objectives to ensure accurate and effective reporting.

• Created and operated real-time data pipelines for real-time data processing and streaming using Apache Kafka, Spark Streaming, and AWS Lambda, enabling faster decision-making with rapid access to data.

• Coached and mentored junior analysts on best practices for data analysis, visualization, and reporting, fostering a high-performing team culture and encouraging continuous professional growth.

• Designed and implemented automated data monitoring and validation systems, ensuring data quality and consistency, improving the integrity of reports and dashboards by detecting and correcting data discrepancies in real-time.

• Assisted in designing a comprehensive data governance framework, ensuring compliance with industry regulations, security controls, and best practices for data management and protection.

• Collaborated with data engineers to design scalable and flexible data architecture that supports the growing needs of the business, contributing to the long-term success of the analytics team.

• Implemented advanced data visualization techniques, such as heat maps, Pareto charts, and geo-visualizations, to provide more descriptive insights into key business metrics and trends.

• Created and scheduled ad-hoc reports for different departments (finance, operations, marketing), ensuring timely access to accurate data that supports critical decision-making.

• Optimized cloud data architecture by migrating data pipelines to AWS and Azure, reducing data processing time by 20% and improving system uptime by 30%.

• Refined data models and reporting templates, providing customizable views for different business teams to meet specific departmental needs, improving reporting efficiency and clarity.

• Collaborated with cross-functional teams, including marketing, sales, and finance, to ensure that data solutions aligned with their requirements and were scalable for future growth.

• Monitored and improved data flow processes within the data warehouse, ensuring optimal system performance and addressing any data pipeline bottlenecks. Environment: Tableau, Power BI, SQL Server, MongoDB, AWS, Azure, Apache Spark, Hadoop, TensorFlow, Keras, Python, SOQL, Salesforce, Apache Kafka, Data Warehousing, ETL processes, Machine Learning.

BI Developer Genpact India Feb 2022 - Aug 2022

• Implemented and executed complex ETL processes using SSIS and SSAS, significantly reducing the time required for extracting, transforming, and loading data during monthly and quarterly reporting cycles, increasing process efficiency by 40%.

• Developed and established in-house Tableau visualizations and dashboards, combining data from Excel, SQL databases, and flat files to track key performance indicators (KPIs) such as operational performance, customer retention, and pipeline sales, allowing for real-time insights into key metrics.

• Led the creation of interactive Tableau scorecards incorporating bar charts, scatter plots, geospatial maps, and Gantt charts, helping senior leadership track project timelines, milestones, and resource allocation for various departments.

• Collaborated with multiple business functions to identify performance metrics and translate them into actionable data models, improving visibility into operational performance and enhancing cross-departmental decision-making.

• Utilized SSIS.NET scripting to integrate internal data systems with external third-party data sources, ensuring seamless data flow, enhanced quality, and higher availability of data for reporting.

• Conducted extensive data analysis using Python, specifically leveraging Pandas and Matplotlib, to uncover trends, generate insights, and prepare data for the development of machine learning models aimed at improving sales predictions and marketing campaigns.

• Enhanced SQL Server performance by developing custom indexes, stored procedures, and functions that optimized data retrieval processes and transaction handling for large datasets, boosting system performance by 30%.

• Implemented data integrity checks through constraints, rules, and referential integrity management in SQL Server, improving the reliability and consistency of reporting data across departments.

• Developed and implemented XML stub data to assist UI testing processes, allowing critical data to be used by front-end developers for creating user interfaces without direct access to live data sources, ensuring smoother development cycles.

• Designed and deployed stored procedures and views to simplify database operations, ensuring data consistency, accuracy, and integrity across various systems and applications.

• Automated routine daily ETL tasks and job tracking through UNIX Shell scripting, reducing manual oversight, increasing production efficiency, and minimizing error rates in the data pipeline and reporting processes.

Environment: SSIS, SSAS, Tableau, Excel, SQL Server, SSIS.NET scripting, Informatica, Python (Pandas, Matplotlib), UNIX Shell scripting, SOAP, XML, Data Warehousing, ETL systems. Associate Software Engineer CSS CORP India May 2020 - Feb 2022

• Updated and built Tableau dashboards to track key metrics within various business segments, providing insights into operational performance, sales, and financial outcomes, which informed key business decisions.

• Developed and implemented ETL methodologies using SQL Server and Excel, efficiently processing and delivering data for reporting purposes on a timely basis, ensuring accuracy and consistency in the reports.

• Performed in-depth data examination to uncover patterns, trends, and anomalies, providing actionable insights that guided strategic planning and improved decision-making across departments.

• Collaborated with business departments to define KPIs and designed tailored reporting solutions, ensuring that reports were aligned with business goals and helped inform departmental decision-making.

• Worked closely with internal stakeholders to translate business requirements into technical specifications, ensuring that the technical data solutions met the needs of the business and contributed to business growth.

• Created and designed ad-hoc reports and data visualizations in Excel and Tableau, providing management with real-time, actionable information that supported critical decision-making processes.

• Normalized, verified, and sanitized raw data, eliminating variances and improving the accuracy and uniformity of data, which enhanced the overall data quality for more reliable analysis.

• Contributed to the development of data warehousing solutions, integrating data from various sources into a unified data repository, enabling comprehensive business analytics across departments.

• Automated data processing tasks using SQL scripts, significantly reducing the manual effort involved in routine reporting and increasing the operational efficiency and effectiveness of day- to-day data handling.

Environment: SQL Server, Excel, Tableau, SQL scripting, Data Warehousing, ETL processes.

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