Azure Data warehousing Consultant
Years of Exp.
1. Azure SQL Data Warehouse administration
2. ETL/ELT using Azure Data Factory
3. Azure Synapse Analytics (formerly SQL Data Warehouse)
4. T-SQL scripting and query optimization
5. Data modeling and schema design in Azure environments
6. Azure Data Lake Storage for big data management
7. Performance tuning and optimization for data warehouses
8. Azure Databricks for data exploration and analytics
8. Azure Databricks for data exploration and analytics
9. Data governance and compliance standards implementation
10. Data encryption strategies in Azure
11. Azure Monitor and Azure Log Analytics for data monitoring
12. PowerShell scripting for automation in Azure
13. Azure Blob Storage for data storage solutions
14. Understanding of columnar storage and distribution techniques in Azure
- 1. Designing and implementing Azure SQL Data Warehouses for clients
2. Developing ETL/ELT pipelines using Azure Data Factory
3. Performance tuning and optimization of Azure data warehouses
4. Collaborating with data architects for data modeling and schema design
5. Implementing security and compliance standards for data governance
6. Leading data migration projects to Azure Synapse Analytics
7. Troubleshooting and resolving issues in Azure data warehouses
8. Conducting regular audits and assessments of Azure data services
9. Providing technical guidance and mentoring to junior engineers
10. Automating deployment and management tasks using PowerShell
11. Collaborating with cross-functional teams for seamless data integration
12. Creating monitoring dashboards using Azure Monitor and Log Analytics
13. Implementing data encryption strategies to ensure data security
14. Conducting performance analysis and implementing optimizations
15. Designing disaster recovery and backup strategies for data warehouses
16. Providing recommendations for cost optimization in Azure data services
17. Participating in client meetings to discuss project requirements and progress
18. Creating documentation for Azure data warehouse architectures and processes
19. Ensuring high availability and scalability of data solutions in Azure
20. Keeping up-to-date with the latest Azure data services and technologies
Manufacturing Data Consolidation
Telecom Data Warehouse Scalability
1. conducted thorough data quality assessments and implemented cleansing strategies for the manufacturing dataset.
2. Collaborated with business stakeholders to define KPIs and developed custom data visualizations for performance tracking.
3. Implemented security measures ensuring compliance with industry-specific data regulations (e.g., ISO standards).
4. Established data retention policies and archival strategies for historical manufacturing data.
5. Conducted performance tuning exercises to optimize query execution and reduce latency in reporting.
6. Provided extensive documentation and training to the internal team for ongoing data management.
7. Led data migration efforts from legacy systems, ensuring minimal disruption to ongoing operations.
8. Conducted regular performance and security audits on the Azure SQL Data Warehouse environment.
9. Implemented machine learning models for predictive maintenance using the consolidated manufacturing data.
1. Conducted in-depth performance profiling and optimization exercises to enhance query efficiency.
2. Implemented data partitioning strategies to enhance data loading and retrieval speed in Azure Synapse Analytics.
3. Established robust monitoring and alerting systems for proactive management of system health.
4. Developed disaster recovery plans and conducted regular drills to validate their effectiveness.
5. Collaborated with vendor teams to evaluate and integrate new technologies for further scalability.
6. Implemented data encryption protocols to ensure the security of sensitive telecom data.
7. Conducted extensive capacity planning and forecasting for future data growth and scalability.
8. Designed and implemented data governance frameworks for telecom-specific regulatory compliance.
9. Facilitated knowledge sharing sessions and workshops to educate teams on best practices in data warehousing.
10. Led data archiving initiatives to maintain optimal performance in a rapidly growing data environment.
Financial Analytics Platform Implementation
1. Implemented advanced data analytics algorithms for predictive financial modeling.
2. Conducted thorough data profiling and cleansing activities to ensure data accuracy and consistency.
3. Collaborated with data scientists to deploy machine learning models on the Azure Synapse Analytics platform.
4. Designed and executed data migration strategies from legacy systems to Azure Synapse Analytics.
5. Established robust data access controls and data masking techniques for sensitive financial data.
6. Conducted extensive performance tuning and optimization for complex financial queries.
7. Implemented streaming analytics for real-time financial data processing and analysis.
8. Conducted training sessions for end-users and stakeholders on utilizing the analytics platform.
9. Established data lineage and data cataloging practices for traceability and audit purposes.
10. Implemented automated data validation processes to ensure the integrity of financial data.
11. Worked closely with compliance officers to ensure regulatory adherence within the financial analytics platform.
MCA – from Kristu Jayanti college
Microsoft Certified: Azure Data Engineer Associate
Microsoft Certified: Azure Solutions Architect Expert
Microsoft Certified: Azure Database Administrator Associate