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Sai Teja Reddy - Data Analyst

saiteja.d01@gmail.com

Location: Saint Paul, Minnesota, USA

Relocation: Yes

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SAI TEJA REDDY saiteja.d01@gmail.com Professional Summary Having 10 years of Professional expertise in SQL, Python, AWS, Tableau and MS Tools to perform Business Operations using technical tools for effective analysis in Data Extraction, Analysis and Cleansing. Innovative and results-driven BI Power App Developer with extensive experience designing and developing Canvas and Model-Driven Power Apps, leveraging robust data models and seamless integration capabilities. Proficient in DAX, SQL, and Dataflows, with a proven track record of delivering scalable solutions that enhance business intelligence and streamline workflows. Expertise in data ingestion and ETL processes, ensuring accurate data consolidation and optimal performance across systems. Expert in Power BI and ability to program in DAX query language to modify data for reporting. Involved in Requirement Gathering, Business Analysis and Development of code, Testing, and implementation of business requirements. Hands-On development of rich and complex Dashboards, Reports, and Visualization using Tableau and AWS Quick Sight. Excellent knowledge in Data Analysis, Data Validation, Data Cleansing, Data Migration, Data Transformation, Data Warehousing, Data Mapping, ETL, Business Intelligence, Data visualization and Reporting and Identifying Data mismatch. Proficient in using Azure Data Factory to efficiently ingest and transform data from various sources into a unified format for analysis. Worked on Amazon EC2, EMR, Amazon S3, Amazon RDS, Redshift, Amazon Elastic Load Balancing, Amazon SNS, and other services of the AWS infrastructure. Extensive experience with T-SQL in constructing Triggers, and tables, Implementing Stored Procedures, Functions, Views, User Profiles, Data Integrity and Data Dictionaries. Proficient in using Hadoop's data ingestion tools like Apache Flume and Sqoop to efficiently bring in large volumes of data from various sources into the Hadoop ecosystem. Performed data cleansing and manipulation by using excel VLOOKUP s, pivot tables and other advance excel functions. Familiar with Agile and SCRUM methodologies. Experienced in utilizing Scala for data analysis tasks to enhance data processing efficiency and perform advanced statistical analyses. Conducted thorough data cleaning, data manipulation and validation using SAS Programming to ensure data accuracy and quality. Skilled in managing Power Platform administration, including security, environment configurations, and licensing, to support enterprise-wide application deployment. Adept at leveraging Microsoft Dataverse and cloud technologies to build scalable, secure, and high-performing business applications. Experienced in integrating APIs and optimizing query performance, driving efficient data workflows and enhanced operational efficiency. Experience in creating visualizations, interactive dashboards, reports, and data stories using Tableau, Power BI and Micro Strategy. Proficient in using Azure Monitor and Azure Data Explorer to monitor data pipelines and performance, ensuring data quality. Performed data comparison between SDP (Streaming Data Platform) real-time data with AWS S3 using Databricks, SQL, and Python. Proficient in Oracle Database management, with hands-on experience in querying, retrieving, and manipulating data using SQL. Orchestrated data integration processes between Oracle databases and other systems, utilizing tools like Oracle Data Integrator (ODI). Technical Skills: Programming Languages Python, R Data Analysis & Business Analysis SQL, Python Data Integration & ETL AWS, Azure Data Factory, Apache Flume, PySpark, informatica Data Visualization Tableau, Power BI, Power Apps, QlikView, Google Analytics Data Warehousing Azure SQL Data Warehouse, Redshift, Hadoop Clouds AWS, Azure Database Management MySQL, Oracle, PostgreSQL, NoSQL, PL/SQL, Snowflake, tSQL Data Cleansing & Quality SAS, MS Excel (VLOOKUP, pivot, advanced functions) Version Control Git, Subversion (SVN), TFS Data Mining & Machine Learning SAS, Python libraries (NumPy, Pandas, SciPy) Reporting Services SQL, SSRS, SSMS, SSIS Data Governance & Metadata Management Azure Data Explorer, Google Analytics Data Profiling & Mapping Complex SQL queries, data validation Data Transformation AWS Glue, DAX query language (Power BI) Statistical Analysis Hypothesis testing, SAS, Python statistical tests Data Validation & Testing Unit testing, integration testing, UAT, Jupyter Notebook Data Visualization Tools Tableau, Power BI, QlikView General Communication, Problem-Solving Big Data Tools Hadoop, Spark, Kafka, Hive Professional Experience Senior Data Analyst Mayo Clinic | Rochester, MN Sep 2024 Present Worked with business requirements analysts/subject matter experts to identify and understand requirements. Performed exploratory data analysis like calculation of descriptive statistics, detection of outliers, assumptions testing, factor analysis in Python and R. Created and optimized both Canvas and Model-Driven Power Apps to deliver business-critical solutions, integrating user-friendly interfaces with complex data operations. Designed robust data models, defined entity relationships, and ensured seamless data integration for scalable app development. Utilized advanced Data Analysis Expressions (DAX) to implement complex calculations and enrich data visualizations in Power BI and Power Apps. Connecting Oracle databases to data visualization tools (e.g., Tableau, Power BI) to create compelling visual representations of data. Worked with Azure Data Factory (ADF) since it is a great SaaS solution to compose and orchestrate Azure data services. Involved in extensive Data Validation, Data Mapping by writing several complex SQL queries and involved in back-end testing and worked with data quality issues. Employed SAS for statistical analysis, hypothesis testing, and data modeling to extract meaningful insights. Conducting training sessions to empower users with QlikView skills, enabling them to explore data independently. Implemented and maintained data storage solutions on Hadoop clusters, ensuring efficient data retrieval and storage. Utilize Python's libraries like NumPy and SciPy to perform statistical analysis, statistical tests, hypothesis testing, and exploratory data analysis, providing data-driven decision support. Connecting various local and live data sources such as excel, Json, and MySQL database in Tableau. Created Hive tables and working on them using Hive QL. Creation of data structure and staging area for dumping the legacy data and interlinking all the segment data for in-depth analysis and closer look. Performed data validations using SQL Developer. Developed and maintained efficient Dataflows to streamline data ingestion into Dataverse and support export flows for external integrations. Created, optimized, and maintained SQL queries to enable sophisticated data manipulation, aggregation, and reporting. ETL Process Automation: Designed and implemented Extract, Transform, Load (ETL) workflows to ensure accurate and timely data consolidation across multiple systems. Used Hadoop's HDFS (Hadoop Distributed File System) for storing vast amounts of structured and unstructured data. Designed and implemented data-driven applications using Django and Flask, providing end-users with interactive tools to visualize and analyze data efficiently. Performed Data analysis and Data profiling using complex SQL on various sources systems. Created EC2 Instances to run automated Python scripts to extract data from the data warehouse into flat files and applied transformations on the flat files for analytical and business validation purposes. Worked closely with the Data governance team and Data Stewards in implementing Metadata management that includes the delivery of Data dictionaries, Data flows, report catalogs, DQ rules. Utilized MongoDB to efficiently store and query large volumes of unstructured data, enhancing data analysis capabilities and enabling data-driven insights for decision-making. Worked on the integration of Snowflake with various data sources, including local and live data sources such as Excel, JSON, and MySQL databases. Created and maintained dashboards using Quick Sight and Tableau for data management and UD compliance. Created interactive and insightful data visualizations using Power BI to help stakeholders make data-driven decisions. Developed complex SQL queries and functions to extract meaningful insights from PostgreSQL databases. Worked with Oracle data warehousing tools like Oracle Data Warehouse, OLAP for multidimensional analysis. Integrated Google Analytics data with other data sources and platforms, enabling a holistic view of user behavior and business performance. Adept at implementing Azure security measures, including Azure AD, to safeguard sensitive data and comply with industry regulations. Maintained detailed GitHub and organized Jupyter Notebook documentation, including code comments, explanations, and visualizations, for team collaboration and knowledge sharing. Implemented ETL platform using Azure Data Factory, Databricks, Data Lake and Azure SQL. Senior Data Engineer Thomson Reuters | Eagan, MN Oct 2021 Aug 2024 Configured and automated cloud-based data infrastructure using Chef and Terraform, ensuring the seamless deployment of services across AWS EC2 instances and on-premises servers. Developed and managed ETL pipelines to automate the extraction of data from various sources, transforming it using Python scripts, and loading it into AWS S3 buckets, ensuring data consistency and availability for downstream processing. Managed and optimized data workflows by writing Chef Recipes/Cookbooks for the deployment and configuration of OS, applications, services, and packages, enhancing data processing efficiency. Developed Python scripts to automate the provisioning and scaling of cloud resources, including EC2, VPC, and other AWS services, ensuring high availability and fault tolerance of data pipelines. Utilized Terraform to automate the creation and management of AWS resources, including S3 buckets, IAM roles, and security groups, ensuring secure and scalable cloud storage solutions. Implemented CI/CD pipelines in Jenkins, integrated with GitHub, and used Ansible playbooks to automate the build, deployment, and configuration processes for data applications. Automated cloud monitoring and logging for data workflows using Nagios, Splunk, and AWS CloudWatch, ensuring the integrity and performance of data systems. Defined and managed Ansible playbooks and roles to automate the continuous delivery process of data applications, enhancing the reliability and efficiency of data processing pipelines. Integrated log monitoring tools, including ELK Stack, for real-time analysis of data processing metrics and logs, facilitating proactive troubleshooting and optimization of data workflows. Data Engineer DirecTV | El Segundo, CA Jul 2019 Sept 2021 Involved in Requirement gathering, Business Analysis, Development of code, Testing, and implementation of business requirements. Creating processes that enhance operational workflow and provide positive customer impact. Involved in conducting Functionality testing, Integration testing, Regression testing and User Acceptance testing (UAT). Involved in designing an Objected Oriented Security model for different Access Groups and assigned different roles to the Users. Working with Unix/Linux systems with scripting experience and building data pipelines. Built AWS Data pipelines for data migration from one DB to another DB. Performed Data Analysis and Data profiling using complex SQL on various source systems including Oracle and Teradata. Scheduled and managed jobs on the Hadoop cluster. Utilizing SQL Server Integration Services (SSIS) to streamline data extraction, transformation, and loading processes, ensuring efficient data management and analysis for informed decision-making. Developed and maintained SAS scripts for automating routine data analysis tasks, enhancing efficiency. into reporting tools like Tableau or Power BI for data analysis and visualization. Oversaw data migration projects, transferring data to PostgreSQL from various sources. Validated already developed Python reports, fixed the identified bugs, and redeployed the same. Managed storage in AWS using S3, created volumes and configured snapshots. Implemented predictive models in SAS and monitored their performance for ongoing improvements. Creating Databricks notebooks using SQL Python and automated notebooks using jobs. Engineered data-driven applications with Django and Flask, creating user-friendly interfaces that interact seamlessly with relational databases to empower end-users in making informed decisions based on real-time data. Utilized Scala to efficiently process and analyze large datasets, leveraging its functional programming capabilities to extract valuable insights and drive data-informed decision-making. Created and run jobs on AWS cloud to extract transform and load data into AWS Redshift using AWS Glue, S3 for data storage and AWS Lambda to trigger the jobs. Developed and tested data processing and machine learning models within Jupyter Notebook and SAP, facilitating experimentation and iterative model improvement. Utilized natural language processing (NLP) techniques to extract valuable insights from unstructured text data, enhancing data analysis capabilities and contributing to more nuanced and context-aware decision-making as a data analyst. Data Engineer / Analyst Merck Pharma | Mumbai, India Aug 2017 May 2019 Worked with management to prioritize business and information needs. Provided a standard process for analysing data across multiple systems and identify erroneous/misaligned data and recommend resolution. Worked on various Python libraries for developing and testing code for data transformation Functions like NumPy, Matplotlib, Panda s data frame, urllib2, MySQL dB for database connectivity. Involved in unit testing to check data consistency. Created data Stories, Reports, and Visualization using Tableau and Power BI. Used feature engineering to enhance model performance, adept at leveraging advanced analytics techniques for comprehensive data exploration, and experienced in applying predictive analytics methodologies to derive actionable insights for informed decision-making. Experienced in large data migration projects from on-prem databases to Azure SQL and Azure Data warehouse. Transformed and reshaped data using SAS transformations for specific analytical needs. Worked with Tableau administrator in managing Production, Test, and Development. Used python APIs for extracting daily data from multiple vendors. Knowledgeable in integrating Hadoop with various data processing ecosystems such as Kafka, Spark, and Flink. Proficient in creating informative charts and graphs in Excel to present data-driven findings in a clear and visually appealing manner. Wrote T-SQL procedures to generate DML scripts to perform the database operations and modified database objects. Collaborated with cross-functional teams to translate business questions into analytical solutions using SAS. Stay updated with QlikView best practices and industry trends, actively seeking opportunities to enhance data analytics processes. We conducted exploratory data analysis (EDA) to uncover meaningful patterns, trends, and insights within the dataset, laying the foundation for informed decision-making and shaping subsequent analytical approaches. Experience in designing and managing data warehouses with Azure SQL Data Warehouse, optimizing data storage and retrieval. Extracted valuable insights from Google Analytics data, identifying trends, user paths, and areas for improvement in digital properties. Utilized Jupyter Notebook for data exploration, performing initial data analysis, and gaining insights into data quality and structure. Implemented ETL platform using Azure Data Factory, Databricks, Data Lake and Azure SQL. Data Engineer Ditech | Delhi, India Jun 2015 Jul 2017 Developed and maintained end-to-end ETL pipelines using Informatica PowerCenter to extract, transform, and load (ETL) data from diverse sources including relational databases, flat files, and APIs into Azure SQL and Azure Synapse Analytics. Led data migration projects from on-premises SQL databases to Azure Synapse Analytics and Azure Data Lake, ensuring smooth integration and seamless data flow using Informatica for efficient transformation and loading. Built and managed Azure Data Factory pipelines to automate and orchestrate data workflows, integrate with Informatica for hybrid cloud environments, and ensure scalability and performance optimization. Designed and implemented data warehousing solutions on Azure, leveraging Informatica PowerCenter to create robust mappings and workflows for loading data into fact and dimension tables. Used Star Schema modelling and Slowly Changing Dimensions (SCD) to ensure accurate historical tracking. Applied performance tuning techniques to Informatica workflows and mappings to optimize data processing, ensuring efficient data transformations and improving system performance for high-volume data loads. Collaborated with cross-functional teams to understand business requirements and translated them into scalable data engineering solutions. Documented technical workflows, data mappings, and best practices to ensure reproducibility and easy handover to teams. Education Details Bachelors in Computer Science and Engineering | Jawaharlal Technological University, India Graduated 2015 Keywords: continuous integration continuous deployment business intelligence sthree database active directory rlang information technology microsoft procedural language California Minnesota