NITHIN KRISHNA ENUGURTHI

LendFast Data Ingestion and Reporting - Credit Union SA (Client)

• Seamlessly transitioned reporting services from Symtrix application to LendFast, focusing on data lineage, reporting development, and comprehensive testing for Credit Union SA (CUSA).
• Developed an SSIS package to ingest data from flat (CSV) files on the network into tables within the on-premises data warehouse.
• Designed and implemented an ETL pipeline based on the medallion architecture, incorporating landing and staging phases.
• Created and maintained a clear audit trail for all ingestion operations.
• Designed and implemented data integrity checks, including datatype verification, referential integrity, nullable fields, and format validations as part of the pipeline.
• Designed the data model for LendFast, ensuring support for downstream reporting while incorporating Slowly Changing Dimension (SCD) Type 2 changes.
• Developed and tested scripts for the entire pipeline and data ingestion process.
• Drafted comprehensive technical documentation, including deployment and maintenance guides.
• Designed and developed Azure Data Factory pipelines for both full and delta data loads from on-premises to Azure SQL Database.
• Implemented the entire data pipeline orchestration using SQL Server Agent job, from ingestion to transformation and loading into Azure SQL DB.

Impacts and Achievements

• Successfully transitioned reporting services, ensuring data integrity and comprehensive testing.
• Developed a dynamic ETL script that simplified table creation and data population, earning praise from senior leadership.
• Designed and implemented Azure Data Factory pipelines, enhancing data management efficiency.
• Recognized by the client for delivering high-quality outputs in a short timeframe, strengthening client relationships.

Hyperspectral Imagery Project for Solar Panel Optimization - RAA (Client)

• Implemented advanced image processing techniques and machine learning algorithms to analyze multidimensional hyperspectral data, enhancing the decision-making process for solar panel installations with insights on environmental factors, roof material properties, and temporal changes.
• Contributed to the development and maintenance of a scalable and secure backend infrastructure utilizing a suite of AWS services (API Gateway, Lambda, S3, DynamoDB, Cognito, SageMaker) for efficient data management, model deployment, and user authentication.
• Engaged in collaborative team efforts including problem-solving sessions, code reviews, and model iteration, driving continuous improvement and ensuring high standards of code quality and project documentation.
• Supported the documentation process of methodologies, models, and testing outcomes, ensuring the project's approaches and results were replicable, well-understood, and accessible for future reference and scaling.

Sustainability Insights Platform:

• Led a team to architect and build the platform's core engine, adept at transmuting activity data into actionable ESG dimensions.
• Successfully implemented Delta Lake as our data storage solution, bolstering the capabilities of our data lake and enabling efficient Change Data Capture (CDC) handling.
• Collaborated closely with cross-functional teams, including Data Scientists, Data Engineers, and Business Analysts, to identify data quality requirements and incorporate them into the data pipeline architecture.
• Devised a flexible data ingestion system compatible with various sources such as databases and SFTP servers, capable of processing both structured and unstructured files.
• Implemented robust data governance framework using AWS Lake Formation, enabling precise control and management of granular-level data access, ensuring data security and compliance.
• Designed & developed a scalable data model, enabling real-time dashboards in AWS QuickSight & Power BI for data-driven decision-making.
• Integrated AWS Textract for parsing PDFs, enabling the capture of high-grade data.
• Engineered a configurable data generator tool to generate domain-specific data as per user requirements.
• Masterfully orchestrated the entire data pipeline utilizing Amazon Managed Workflows for Apache Airflow (MWAA), crafting effective DAG scripts for optimized workflow management.

Impacts & Achievements:

• Pioneered the use of multi-threading in PDF extraction via Textract, achieving an impressive reduction in processing time from 15 minutes to just 3 minutes for 120 documents.
• Recognized for outstanding problem-solving skills and proactive approach in resolving complex data quality issues, positively impacting the efficiency of the data pipeline and downstream processes.
• Commended by the Engagement Leader for creating a versatile Data Generator tool, serving as a crucial element in building data-driven application POCs.
• Innovatively developed a standalone emission calculator in AWS Lambda, contributing to the understanding and reduction of carbon emissions.

Customer Insights Engine:

• Designed and developed a metadata-driven transformation pipeline using Pyspark AWS Glue job, with easy customization via a YAML file.
• Engineered a Graph data builder to automate creation of graph edges and nodes in AWS Neptune per graph configuration file.
• Orchestrated the Customer Insights Engine with AWS Step function, enabling seamless integration of all components.
• Utilized Pyspark to load data into AWS DynamoDB, feeding an ML model in AWS Sagemaker endpoint.

Impacts:

• Created standalone, industry-agnostic components, with market potential for the firm.
• Facilitated diverse application development via a data and config-driven approach.
• Improved engine execution efficiency through dynamic operations based on FULL or DELTA load.

DocMap:

• Developed an inference pipeline using S3, AWS Step functions, Docker services, and Python, to classify finance documents in the Banking sector.
• Built preprocessing scripts to gather and clean data, addressing the finance sector's challenges.

Achievements:

• Recognized by project Data Scientist for creating a unique ID system enabling easy traceability to raw documents after classification.
• Developed a visualization demonstrating time efficiency from tokenization to classification, acknowledged by the Managing Director.

SINAMICS G120X:

• Developed the Field Device Integration (FDI) package for the SIMATIC PCS7 application, facilitating configuration and commissioning of G120X hardware.
• Engineered key features of Application Start-up and Control Status Word-I/II in the G120X FDI package v2.2.
• Created user-friendly interface plugins using HTML and CSS, enhancing product usability.
• Designed and implemented the DictGenerator tool, consolidating dictionary content from multiple language files into a single, accessible file.

Accomplishments:

• Conceived and introduced a real-time drive status LED in the Application Start-up feature, recognized by the Product Manager as a significant industrial application use case.

Transformer:

• Developed a Python-based tool for log analysis, transforming XML log files into concise, informative reports on test case status.
• Utilized XMLschema and Regex libraries for data wrangling and output generation in Excel format.
• Managed daily task allocation within the team, driving optimal productivity.
• Collaborated within an Agile Development Environment, spanning from requirement analysis to delivery phase.
• Contributed to test case design using pytest, reinforcing development quality and reliability.