- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
- ETL
- SQL
- Azure
- Linux
- Communication
- Power Bi
- Agile
- Express
- Data Quality
- Automation
- Architected Azure Data Factory pipelines processing 2M+ records daily with 99.9% uptime.
- Improved data quality by implementing automated validation checks and alerts on critical datasets.
- Collaborated with analytics teams to reduce report refresh cycle from 4 hours to 45 minutes.
- Documented ETL workflows in Confluence, improving onboarding time for new data engineers.
- Optimised SQL queries used in Power BI dashboards, reducing average execution time by 30%.
