Sukesh Gajawada Email & Phone Number

Dallas, Tx, Us

Durant, Oklahoma, United States

• Mastered a wide array of Azure technologies, including HDInsight, Databricks, Data Lake, Blob Storage, Data Factory, Synapse Analytics, Azure SQL Database, and SQL Data Warehouse, to streamline cloud operations and data management.• Designed and automated custom input adapters using Spark, Sqoop, and Oozie, significantly enhancing data ingestion from RDBMS to Azure Data Lake, showcasing a blend of innovation and efficiency in data handling.• Played a pivotal role in the creation of automated workflows for daily incremental data loads, facilitating seamless data transition from traditional RDBMS systems to more scalable data lake solutions, thus optimizing data availability and reliability.• Executed comprehensive ETL (Extract, Transform, Load) processes, utilizing Azure Data Factory, T-SQL, Spark SQL, and U-SQL for Azure Data Lake Analytics, ensuring efficient and scalable data movement and transformation strategies.• Engineered and deployed data pipelines in Azure Data Factory, targeting enhanced ETL processes from diverse sources such as Azure SQL, Blob storage, and Azure SQL Data Warehouse, thereby ensuring data integrity and accessibility.• Crafted and deployed JSON scripts in Azure Data Factory, leveraging SQL Activity for efficient data processing and integration, highlighting technical proficiency and advanced deployment capabilities.• Demonstrated deep understanding of data ingestion and orchestration using Airflow Operators and relevant Python libraries, enhancing data flow and operational efficiency.• Analyzed SQL scripts and implemented solutions using PySpark, focusing on optimizing data processing and analytics workflows.• Extensively used Databricks notebooks for interactive analytics, employing Spark APIs to facilitate advanced data analysis and insights.• Integrated data across various sources including MongoDB, MS SQL, and cloud platforms, using Azure Data Factory, SQL API, and Mongo API, to ensure a unified data ecosystem.

• Designed scalable data pipelines using Python, ensuring efficient data extraction, transformation, and loading (ETL) processes across various data sources to support data warehousing and analytics, processing over 10 MB of data daily.• Developed big data solutions utilizing Apache Spark, optimizing data processing performance for large datasets and enabling real-time analytics capabilities to enhance data-driven decision-making.• Successfully executed query optimizations on AWS, utilizing Amazon RDS and Amazon Redshift, to improve database and data warehouse performance.• Utilized AWS Athena to manipulate CSV data files stored in AWS S3, applying Scala queries for proficient data extraction and transformation, showcasing versatility in data handling methodologies.• Formulated and implemented Python solutions to extract data from AWS S3 and populate it into SQL Server, directly supporting business team requirements through effective data integration strategies.• Managed Cassandra databases, ensuring high availability, fault tolerance, and efficient data storage and retrieval mechanisms, which improved the reliability and performance of data-driven applications.• Utilized Terraform for automating infrastructure provisioning, improving deployment efficiency from 2 days to 2 hours, ensuring consistent and reproducible infrastructure environments, and reducing manual configuration errors.• Created interactive and insightful dashboards in Tableau, visualizing key metrics and providing data-driven insights to stakeholders for informed decision-making, which enhanced business intelligence and strategic planning.

Hyderabad, Telangana, India

• Conducted in-depth data analysis using Python and SQL to extract insights from complex business datasets, identifying key trends and operational inefficiencies and presenting findings to senior management, leading to significant process efficiency improvements• Designed and maintained scalable MongoDB databases to effectively manage and store large volumes of operational data, implementing data validation rules and indexing strategies, enhancing query performance and data reliability• Developed comprehensive dashboards and reports using Tableau and Matplotlib, visualizing critical KPIs and business metrics for 5 key departments and driving data-informed decisions across departments, increasing overall productivity• Engineered robust ETL pipelines using Talend and Azure Data Factory, integrating data from multiple sources into a centralized data warehouse, streamlining data workflows, reducing data processing time, and enhancing data quality• Leveraged big data technologies, including HDFS and Azure Databricks, to process and analyze large-scale datasets, applying advanced analytics techniques to uncover valuable business intelligence and contributing to market share growth• Collaborated closely with cross-functional teams in an Agile environment to identify and implement process improvements, utilizing MS Excel for ad-hoc analysis and reporting, optimizing business operations, and achieving significant annual cost savings.

• Engineered data pipelines using Informatica PowerCenter and AWS Glue to extract data from multiple banking systems, including core banking, credit card, and loan management platforms, as part of the Financial Data Integration and Analytics Platform.• Deployed a high-performance Oracle database on AWS RDS as the central repository for integrated financial data, implementing security measures and optimizing query performance to handle 50+ concurrent users. • Coded sophisticated Python scripts for data cleansing and transformation, incorporating algorithms for normalization, deduplication, currency conversion, and format standardization across diverse financial datasets. • Architected a scalable AWS Redshift data warehouse with an optimized schema to facilitate complex analytical queries on large-scale financial data, enabling rapid analysis of historical trends. • Constructed an extensive suite of interactive Power BI dashboards for financial reporting, featuring real-time updates, drill-down capabilities, and customizable visualizations for various stakeholder groups. • Orchestrated Hadoop and Impala clusters to process 2 PB of historical transaction data, implementing partitioning strategies and query optimization techniques for petabyte-scale datasets. • Established a GitHub repository for version control, implementing branching strategies, code review processes, and automated testing to maintain code quality and documentation of data models and ETL processes.

• Extracted historical inventory and sales data from Cipla's ERP system, 5 supplier databases, and 3 warehouse management systems, then integrated this data into a centralized MySQL database hosted on AWS RDS using custom-developed Python scripts for automated extraction and transformation. • Executed SQL techniques to streamline data queries, enhancing overall data analysis efficiency and generating actionable insights for informed decision-making.• Created interactive data visualizations using Tableau, effectively supporting strategic decision-making processes within the organization.• Used Python scripting to automate data collection, transformation, and analysis tasks, enabling efficient handling of large datasets and complex calculations.• Performed comprehensive data cleaning and preprocessing using NumPy and Pandas, addressing missing values, outliers, and inconsistencies and extensive exploratory data analysis to uncover critical insights into inventory turnover rates, demand patterns. • Designed interactive Power BI dashboards providing real-time visibility into inventory levels, forecast accuracy, and supplier performance metrics, complemented by detailed MS Excel reports summarizing key insights for supply chain managers. • Architected a robust cloud infrastructure utilizing AWS services, including EMR for large-scale data processing of 1 TB datasets and complex calculations, and S3 for secure, scalable storage of raw and processed data, ensuring efficient analysis and retrieval.• Collaborated closely with cross-functional teams including supply chain managers, procurement specialists, while actively participating in Agile (Scrum) ceremonies to ensure project alignment and effective communication of data-driven insights and recommendations.• Created and maintained a centralized Git repository for the project, ensuring all code and documentation were stored in a secure, version-controlled environment.

Master Of Science - Ms, Information Technology Management, 3.82

Bachelor Of Technology, Electronics And Instrumentation Engineering

Activities and Societies: Convergence Core Team

Education record

Activities and Societies: Literary Secretary