Anandan Kaliyamoorthy

Cloud Data Engineer with 8+ Years of Proven Expertise accomplished professional specializing in end-to-end data engineering solutions. In-depth understanding of the business process models underlying these domains and leveraging skills in AWS Solutions Architect Associate and Tableau Desktop Specialist certifications, along with proficiency in Python, R, SQL, and DAX programming languages, and analytical tools such as Power BI, Tableau, AWS, Microsoft Azure, SQL Server Data Tools, RStudio, and Microsoft Excel. Extensive experience in business analysis, requirement gathering and eliciting efforts for application development projects including Azure DevOps practice involving Agile, Waterfall methodologies. Participated in different levels of the SDLC cycles – Analyze, Plan, Design, Develop, Test and Deploy in the waterfall and Agile model. Expert Data Manipulator proficient in Python, R, SQL, Excel, and Tableau for advanced data manipulation. Process Improvement Advocate track record of driving process improvements through comprehensive data analysis. High-Impact Reports and Dashboards proven experience in delivering high-impact reports and dynamic dashboards. Azure Data Engineer at Wip ro Technologies leading ETL data pipeline operations with a focus on Azure technologies. Technological Expertise hands-on experience with Azure Databricks, Data Factory, Snowflake, Spark (Scala, Python), and more. Designed and Developed ETL Processes in AWS Glue to migrate Campaign data from external sources like S3, ORC/Parquet/Text Files into AWS Redshift. Worked on ETL Migration services by developing and deploying AWS Lambda functions for generating a serverless data pipeline which can be written to Glue Catalog and can be queried from Athena. ELT/ETL Pipeline Development expertise in developing ELT/ETL pipelines, optimizing data fetching, and deploying CI/CD frameworks. Programming Proficiency strong programming skills in Python, Scala, and proficiency in SQL for data warehousing and analysis. Experienced in Data Architecture and data modeling using Erwin, ER-Studio and MS Visio. Experience in coding SQL for developing Procedures, Triggers, and Packages. Experience in Dimensional Data Modeling Star Schema, Snow-Flake Schema, Fact and Dimensional Tables, concepts like Lambda Architecture, and Batch processing. Experienced in python data manipulation for loading and extraction as well as with python libraries such as NumPy, SciPy and Pandas for data analysis and numerical computations. Extensive knowledge of Data Modeling, Data Conversions, Data integration and Data Migration. Experience in importing and exporting data using Sqoop from HDFS to Relational Database Systems (RDBMS)- Oracle, DB2 and SQL Server and from RDBMS to HDFS. Well experienced in Normalization, De-Normalization and Standardization techniques for optimal performance in relational and dimensional database environments. Solid understanding of AWS, Redshift, S3, EC2 and Apache Spark, Scala process, and concepts. Work experience with UNIX/Linux commands, scripting and deploying the applications on the servers. Collaboration and Teamwork adept at collaborating with cross-functional teams and stakeholders in various Data Engineering roles. Currently pursuing a master’s in data science for continuous skill enhancement. Career Aspiration Committed to professional growth within the field of Data Engineering, aiming to contribute to the development and optimization of robust data infrastructure. Developed SSAS Cubes, including Aggregation, KPIs, Measures, Partitioning Cube, and Data Mining Models. Deployed and processed SSAS objects for effective Business Intelligence. Created ad hoc reports and reports with complex formulas. Executed queries on the database for Business Intelligence purposes. Developed Parameterized, Chart, Graph, Linked, Dashboard, Scorecards, and Cascading reports using SSRS on SSAS Cube. Demonstrated flexibility, enthusiasm, and a project-oriented approach as a team player. Exhibited excellent written, verbal communication, and leadership skills, contributing to the development of creative solutions for challenging client needs. Responsive expert experienced in monitoring database performance, troubleshooting issues and optimizing database environment. Possesses strong analytical skills, excellent problem-solving abilities, and deep understanding of database technologies and systems. Equally confident working independently and collaboratively as needed and utilizing excellent communication skills. Detail-oriented Data Engineer 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. Background includes data mining, warehousing and analytics. Proficient in machine and deep learning. Quality-driven and hardworking with excellent communication and project management skills. Organized and dependable candidate successful at managing multiple priorities with a positive attitude. Willingness to take on added responsibilities to meet team goals. Hardworking and passionate job seeker with strong organizational skills eager to secure entry-level Data Engineer position. Ready to help team achieve company goals. Detail-oriented team player with strong organizational skills. Ability to handle multiple projects simultaneously with a high degree of accuracy. To seek and maintain full-time position that offers professional challenges utilizing interpersonal skills, excellent time management and problem-solving skills.

• Extract Transform and Load data from Sources Systems to Azure Data Storage services using a combination of Azure Data Factory, T-SQL, Spark SQL and U-SQL Azure Data Lake Analytics
• Data Ingestion to one or more Azure Services - (Azure Data Lake, Azure Storage, Azure SQL, Azure DW) and processing the data in Azure Databricks
• Designed ETL data flows using SSIS, creating mappings and workflows for extracting data from SQL Server
• Conducted Data Migration and Transformation from Access/Excel Sheets using SQL Server SSIS
• Efficiently implemented Dimensional Data Modeling for Data Mart design, identifying Facts and Dimensions
• Developed fact tables and dimension tables, incorporating Slowly Changing Dimensions (SCD)
• Implemented robust error and event handling mechanisms, including Precedence Constraints, Break Points, Check Points, and Logging
• Built Cubes and Dimensions with different Architectures and Data Sources for Business Intelligence
• Applied thorough knowledge of Features, Structure, Attributes, Hierarchies, and Star/Snowflake Schemas of Data Marts.

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