Mughees Ulfat

Designed and implemented ETL and ELT pipelines using Python and Azure Data Factory for efficient data ingestion and integration.
Managed large-scale data migration from on-premises systems to Microsoft Azure, ensuring data integrity and security.
Utilized Databricks and Spark for scalable big data transformations, optimizing performance on large datasets.
Developed optimized SQL queries, views, and indexing strategies to enhance database performance.
Created data models to structure and analyze raw data for advanced reporting and analytics.
Collaborated with stakeholders to gather requirements, deliver tailored data solutions, and provide and ensure seamless data integration and reporting.

Designed and implemented ETL and ELT pipelines using Python and Azure Data Factory for efficient data ingestion and integration. Managed large-scale data migration from on-premises systems to Microsoft Azure, ensuring data integrity and security. Utilized Databricks and Spark for scalable big data transformations, optimizing performance on large datasets. Developed optimized SQL queries, views, and indexing strategies to enhance database performance. Created data models to structure and analyze raw data for advanced reporting and analytics. Collaborated with stakeholders to gather requirements, deliver tailored data solutions, and ensure seamless data integration and reporting.

Developed ETL pipelines to extract, transform, and load data from WordPress databases into PostgreSQL/MySQL.
Implemented BI solutions, integrating and organizing data from multiple sources to support reporting and analytics.
Optimized SQL queries and indexing strategies, reducing database load and improving query execution times.
Designed data models to structure and enhance raw website data, enabling advanced business intelligence and reporting.
Led a team to develop a system collecting data from 2000+ WordPress sites, ensuring quality and timely delivery.
Developed and integrated APIs to sync data between WordPress sites and external applications, streamlining information flow.

Developed ETL pipelines to extract, transform, and load data from WordPress databases into PostgreSQL/MySQL. Implemented BI solutions, integrating and organizing data from multiple sources to support reporting and analytics. Optimized SQL queries and indexing strategies, reducing database load and improving query execution times. Designed data models to structure and enhance raw website data, enabling advanced business intelligence and reporting. Led a team to develop a system collecting data from 2000+ WordPress sites, ensuring quality and timely delivery. Developed and integrated APIs to sync data between WordPress sites and external applications, streamlining information flow.

Developed and maintained data pipelines using Python and PostgreSQL for efficient data extraction, transformation, and loading (ETL).
Integrated external and internal APIs to ingest and process real-time and batch data.
Automated repetitive Python tasks to improve workflow efficiency and reduce manual intervention.
Deployed and managed code execution on Virtual Machines (VMs), ensuring reliability and scalability.
Designed and optimized database schemas to support analytics and reporting needs.
Client-facing role involving regular communication to understand business needs and data requirements.
Participated weekly meetings with clients and BI teams to ensure transparency, track progress, and maintain data accuracy.
Collaborated closely with BI teams to align data pipelines with reporting and dashboard needs.
Monitored data flows and debugged to resolve pipeline failures and ensure data integrity.
Partnered with cross-functional teams to gather requirements and deliver tailored, data-driven solutions.

Developed and maintained data pipelines using Python and PostgreSQL for efficient data extraction, transformation, and loading (ETL). Integrated external and internal APIs to ingest and process real-time and batch data. Automated repetitive Python tasks to improve workflow efficiency and reduce manual intervention. Deployed and managed code execution on Virtual Machines (VMs), ensuring reliability and scalability. Designed and optimized database schemas to support analytics and reporting needs. Client-facing role involving regular communication to understand business needs and data requirements. Participated in weekly meetings with clients and BI teams to ensure transparency, track progress, and maintain data accuracy. Collaborated closely with BI teams to align data pipelines with reporting and dashboard needs. Monitored data flows and debugged to resolve pipeline failures and ensure data integrity. Partnered with cross-functional teams to gather requirements and deliver tailored, data-driven solutions.