Nagaraju Vodeti

8+ years of IT experience working as a data engineer in the cloud, developing applications using Big Data Warehousing, ETL, data modeling, and other essential techniques. Gained valuable expertise with AWS by utilizing more than 25 services and created several data pipelines by combining Lambda, Step Functions, Glue, Kinesis, EMR, and Kafka to streamline processes. Practical knowledge of the following: Azure Cloud Services (PaaS & IaaS), Azure Synapse Analytics, SQL Azure, Data Factory, Azure Analysis Services, Application Insights, Azure Monitoring, Key Vault, and Azure Data Lake. Extensive knowledge of Dimensional Data Modeling, Relational Data Modeling, Star Schema/Snowflake Modeling, FACT & Dimensions Tables, Physical & Logical Data Modeling, and Data Analysis. Expertise in Python data extraction and manipulation and widely used python libraries like NumPy, Pandas, and Matplotlib for data analysis. Vast expertise utilizing Talend and created data for ETL methodologies such as Data Profiling, Migration, Extraction, Transformation, and Loading. Practical experience in Data Engineering disciplines such as Data Lake, Datawarehouse, Reporting, and Analytics with Data Storage, Data Ingestion, Batch Processing, Stream Processing, and Real-Time Message Ingestion. Created Spark tasks that successfully conducted different data transformations on the source data using Spark Data Frame and Spark SQL APIs while processing the actual source files. Expertise in the development of various reports and dashboards using various Tableau and Power Bi Visualizations tools. Knowledge of data warehousing and ETL tools like Informatica. Proficient in developing complicated SQL and PL/SQL for designing tables, views, indexes, stored procedures, and functions. Experience working with databases like Teradata and Oracle. Worked on version control tools like Bit-Bucket, GIT, and SVN. Knowledge of the NoSQL databases MongoDB, Cassandra, and HBase Skilled in creating relational databases like Oracle, DB2, MySQL, and MSSQL Server and writing SQL queries, stored procedures, functions, packages, tables, views, and triggers. Experience developing Hadoop-based applications using HDFS, MapReduce, Spark, Hive, Sqoop, HBase, and Oozie. Knowledge of real-time data streaming methods like Spark Streaming and Kafka. Good Knowledge of CI/CD using containerization technologies like Docker and Kubernetes. Knowledge of Waterfall project management and Agile/Scrum development techniques. Working knowledge of many operating systems, including Windows, Linux, UNIX, and Ubuntu

Diligent Desired Position with robust background in data engineering and proven ability to design and implement complex data pipelines. Successfully contributed to optimizing data architecture and enhancing data processing efficiencies. Demonstrated expertise in big data technologies and proficiency in Python and SQL.

Data engineering professional poised to add significant value through comprehensive experience in developing scalable data solutions. Noted for strong team collaboration and adaptability in fast-paced environments. Reliable in driving results with key skills in data modeling, ETL processes, and cloud-based data platforms.

Experienced with building and maintaining data pipelines to ensure seamless data flow. Utilizes advanced knowledge of big data technologies to drive data-driven decision-making. Track record of enhancing data architecture for improved performance and reliability.

Senior engineering professional with deep expertise in data architecture, pipeline development, and big data technologies. Proven track record in optimizing data workflows, enhancing system efficiency, and driving business intelligence initiatives. Strong collaborator, adaptable to evolving project demands, with focus on delivering impactful results through teamwork and innovation. Skilled in SQL, Python, Spark, and cloud platforms, with strategic approach to data management and problem-solving.

Detail-oriented Job Title designs, develops and maintains highly scalable, secure and reliable data structures. Accustomed to working closely with system architects, software architects and design analysts to understand business or industry requirements to develop comprehensive data models. Proficient at developing database architectural strategies at the modeling, design and implementation stages.

Experienced leader with strong background in guiding teams, managing complex projects, and achieving strategic objectives. Excels in developing efficient processes, ensuring high standards, and aligning efforts with organizational goals. Known for collaborative approach and commitment to excellence.

Microsoft Azure Data Engineer and Aws solutions architect