MARUF MUHAMMAD

• Designed and developed scalable ETL/ELT pipelines using Azure Data Factory and SQL Server.
• Built automated ADF pipelines to ingest structured, semi-structured, and unstructured data.
• Developed MERGE-based fact and dimension table loads, processing millions of daily records.
• Implemented DSK-based logic to standardize and unify data across multiple ERP systems.
• Designed staging and transformation layers supporting business key classification and complex mapping rules.
• Migrated large SQL datasets to Azure SQL Database and Azure Blob Storage with automated workflows.
• Performed extensive database audits and optimized historical data to improve storage usage and reporting accuracy.
• Diagnosed and resolved complex SQL issues including deadlocks, blocking, long-running queries, and stale statistics affecting nightly ETL loads.
• Improved SQL performance by rewriting inefficient queries, optimizing execution plans, and eliminating unnecessary table scans.

• Optimized large-scale SQL transformations using temp tables and CTE refactoring.
• Enhanced data quality by creating reconciliation datasets verifying staging vs fact table accuracy.
• Developed optimized MERGE operations for high-volume Fact and Dimension tables.
• Tuned queries by eliminating scalar bottlenecks, minimizing DISTINCT usage, and pushing filters down.
• Refactored long-running ETL processes, reducing runtime from hours to minutes.
• Designed indexing strategies (clustered, nonclustered, filtered, covering) for high-frequency ETL loads.
• Implemented batch-based updates and deletes using WHILE loops to prevent lock escalation.
• Collaborated with engineering, reporting, and product teams to refine complex ETL logic and align with evolving business rules.
• Built automated monitoring/alerting scripts to detect query failures, blocking, and long-running sessions affecting warehouse loads.

• Developed and maintained SSIS packages for data extraction, transformation, and loading.
• Automated SSIS package execution using SQL Server Agent, Windows Scheduler, and custom workflows.
• Improved SSIS performance by 50% through parallel processing and optimized SQL queries.
• Built custom SSIS components and C# tasks to support advanced business rules.
• Integrated XML, JSON, and flat-file sources into enterprise pipelines.
• Implemented dynamic SSIS configurations enabling seamless DEV/QA/PROD deployments.
• Migrated legacy DTS/SSIS packages to modern versions with substantial performance gains.
• Developed robust logging, error-handling, and alerting frameworks inside SSIS packages to minimize downtime.
• Collaborated with QA, data governance, and business teams to ensure data accuracy and compliance with financial regulations.

• Tuned stored procedures, UDFs, and queries for significant performance improvements.
• Designed Azure SQL schemas and supported cloud migration projects.
• Developed Power BI dashboards and optimized data models for Finance and Management teams.
• Implemented table partitioning strategies to support large-scale analytics.
• Automated generation of insights using Power BI and SQL-driven pipelines.
• Partnered with Finance, Accounting, and Operations stakeholders to translate business requirements into optimized SQL logic and BI models.
• Implemented incremental loading strategies to reduce Power BI dataset refresh times and improve gateway performance.

• Developed SQL tables, views, stored procedures, and indexing structures.
• Conducted performance tuning and database optimization to support mission-critical systems.
• Normalized databases and enforced referential integrity using primary/foreign keys.
• Implemented SQL-based auditing and automated reporting for internal stakeholders.
• Implemented scheduled SQL Agent jobs for automated data refreshes, archival processes, and daily validation checks across critical systems.
• Improved system stability by updating stale statistics, rebuilding fragmented indexes, and implementing proactive database maintenance routines.

• Developed SQL scripts, triggers, and views for enterprise healthcare applications.
• Built and maintained SSIS packages for incremental data warehouse loads.
• Created SSRS reports and SSAS star schema cubes.
• Integrated data from Excel, DB2, Flat Files, SQL Server, and Raw Files into the warehouse.
• Improved query performance in clinical reporting systems by tuning long-running SQL procedures and optimizing joins, filters, and indexing strategies.
• Automated routine data quality monitoring by creating SQL-based discrepancy checks between source systems and the data warehouse.