T Harish Kumar

Data Engineer with 6+ years of experience designing and developing ETL pipelines, data-processing solutions, database applications, reporting systems, and backend services across healthcare, government, education, and technology environments. Strong hands-on experience building ETL and data integration workflows using Python, SQL, SQL Server, and SSIS to extract, clean, validate, transform, and load enterprise datasets. Skilled in Python, SQL, T-SQL, and Microsoft SQL Server, with practical experience writing complex queries, stored procedures, views, data transformations, validation logic, and performance-focused database solutions.

Experienced in designing data pipelines, data models, reusable processing frameworks, and source-to-target mappings while handling data cleansing, reconciliation, quality checks, and exception handling. Built analytical and operational reporting solutions with Power BI, SSRS, SQL Server, and Python, helping teams access reliable datasets, dashboards, and reports for business decision-making. Worked with healthcare, health insurance claims, HR, and enterprise datasets, supporting data ingestion, ETL processing, database development, data quality, backend integration, and reporting needs.

Comfortable working with SQL Server, MongoDB, and Firebase Cloud Firestore, along with REST APIs and backend development using .NET/C#, Node.js, and Express.js for data-driven applications. Supported the full data engineering lifecycle, including requirements analysis, architecture design, data ingestion, ETL development, database implementation, testing, performance tuning, reporting, troubleshooting, production support, and Agile collaboration.

Data Engineer at IQLogg Inc. (2026-03 – Present)

State of Virginia Project

• Designed and built an end-to-end data architecture and ETL framework using Python and SQL Server to ingest, process, transform, and store HR datasets for enterprise reporting and analytics.
• Built Python ETL pipelines to extract HR data from source datasets, clean and transform records, apply business rules, and load standardized data into SQL Server.
• Designed SQL Server tables, views, stored procedures, and T-SQL queries to organize and process employee, workforce, and HR-related datasets.
• Developed reusable Python modules for data ingestion, transformation, validation, cleansing, and loading to keep recurring HR data-processing workflows consistent and maintainable.
• Added data-quality checks to identify missing values, duplicate records, formatting issues, invalid data types, and business-rule exceptions before loading processed datasets into reporting tables.
• Built Power BI dashboards and reports from curated SQL Server datasets to help stakeholders review workforce information, HR metrics, trends, and operational reporting needs.
• Created SQL queries, views, stored procedures, and reporting datasets for Power BI while improving retrieval efficiency and keeping business logic consistent across reports.
• Added error handling, logging, reconciliation, and exception tracking within Python ETL workflows to monitor pipeline runs, troubleshoot failures, and improve recurring data loads.
• Worked with business stakeholders and technical teams to translate HR data and reporting needs into source-to-target mappings, transformation rules, database structures, ETL workflows, and Power BI reports.
• Supported the full data engineering lifecycle, including requirements analysis, architecture design, ingestion, ETL development, SQL Server implementation, validation, performance tuning, reporting, testing, troubleshooting, and production support.

Data Engineer /.NET Developer at AlphaTech (2025-06 – 2026-02)

Cigna Healthcare Project

• Developed and maintained data-processing and backend solutions using Python,.NET, C#, and SQL Server to support healthcare workflows, reporting, and enterprise data operations.
• Wrote and optimized T-SQL queries, stored procedures, views, joins, and database objects to prepare healthcare data for applications and analytical reporting.
• Built data-processing workflows to extract, validate, transform, and load healthcare datasets between source systems, SQL Server, backend applications, and reporting layers.
• Used Python to transform healthcare datasets, automate recurring reporting tasks, and prepare structured data for downstream analysis and visualization.
• Built Power BI reports and dashboards from SQL Server and processed healthcare datasets, giving stakeholders visibility into operational metrics, trends, and business performance.
• Developed backend services and REST APIs using.NET and C# to support data exchange between application components, SQL Server databases, processing workflows, and reporting systems.
• Added data validation, cleansing, reconciliation, and exception-handling logic with SQL and Python to identify data-quality issues and maintain consistency across healthcare datasets and reports.
• Improved database and reporting performance by tuning SQL queries, stored procedures, indexes, data-access logic, and dataset preparation processes.
• Investigated data discrepancies, reporting issues, failed processing workflows, and backend defects by tracing problems across Python, SQL Server,.NET, and Power BI components.
• Worked with developers, analysts, QA engineers, and healthcare stakeholders in an Agile environment to turn business requirements into data pipelines, backend services, database solutions, and analytical reports.

Backend / Data Engineer at Intelagen (2024-11 – 2025-06)

• Designed and built backend services for a student identity and verification platform used by universities and colleges to manage student information, digital identities, and verification workflows.
• Developed REST APIs to connect frontend applications, backend services, and data stores for student onboarding, profile management, identity verification, and institutional workflows.
• Designed database structures and data models to organize student profiles, institutional details, verification records, application metadata, and related transaction data.
• Built backend data-processing workflows to ingest, validate, transform, and store student information consistently across application components.
• Implemented authentication, authorization, and role-based access controls for students, university administrators, and other authorized users.
• Developed reusable backend services and data-access components for CRUD operations, querying, filtering, validation, and business-rule processing across student and institutional datasets.
• Added validation, error handling, logging, and exception tracking to improve backend reliability and make troubleshooting easier.
• Improved database and backend performance by reviewing query patterns, API workflows, and data-access logic as student data volumes increased.
• Integrated backend components with internal and external services through APIs to support secure exchange of student and verification data across the platform.
• Worked with product and engineering teams in an Agile startup environment to turn student identity-management requirements into backend features, while supporting architecture, development, testing, debugging, and deployment.

Backend / Data Engineer at YourBeat Inc. (2024-05 – 2024-10)

• Designed and built backend services for a music platform using Node.js, Express.js, and MongoDB, supporting artist onboarding, music uploads, content management, and royalty-related workflows.
• Designed MongoDB collections, document schemas, relationships, and indexes to manage artist profiles, music metadata, user information, uploaded content, and transaction data.
• Developed REST APIs with Node.js and Express.js to connect the React frontend, backend services, and MongoDB database across core platform features.
• Built backend workflows to process music metadata and artist-related data, including validation and transformation before storing information in MongoDB.
• Implemented authentication and authorization to control access to artist accounts, user profiles, protected API endpoints, and backend resources.
• Developed service-layer components for CRUD operations, filtering, querying, and aggregation across MongoDB collections used by the platform.
• Added backend logic for royalty-related data workflows, helping connect artist information, music content, and tracking data for payment processing.

MS in Information Technology, Arizona State University, Arizona, USA