Amber Sharma

• Designed and developed Snowflake SQL views and Microsoft Fabric Warehouse/Lakehouse views to deliver curated, reporting-ready datasets to the Power BI team, ensuring consistent and optimized data consumption.
• Performed source-to-target data mapping (STTM) by analyzing source systems, mapping business attributes, and implementing transformation logic for regulatory reporting datasets across Snowflake and Fabric.
• Developed complex SQL (joins, CTEs, window functions, aggregations) in Snowflake and Fabric SQL endpoints to transform, cleanse, and validate large volumes of insurance data.
• Built ingestion and orchestration pipelines using Fabric Data Factory pipelines and Dataflows Gen2, landing data into OneLake and Lakehouse Delta tables following a medallion (Bronze–Silver–Gold) architecture.
• Developed PySpark/Spark SQL notebooks in Microsoft Fabric for large-scale transformations, data enrichment, and incremental loads into Lakehouse tables.
• Built and maintained ETL/ELT workflows extracting data from multiple source systems, applying business transformation rules, and loading curated datasets into Snowflake and Fabric Lakehouse/Warehouse layers.
• Implemented business transformation rules to standardize, enrich, and prepare data for downstream regulatory reporting and analytics.
• Created reusable data models, Gold-layer reporting views, and semantic models (Direct Lake / Import mode) to support regulatory reporting while improving query performance and data consistency.
• Created and managed Job IDs, pipeline schedules, and execution workflows, monitoring batch runs, handling failures, and ensuring successful scheduled data loads.
• Performed data quality validation by reconciling source and target datasets, identifying inconsistencies, and resolving data integrity issues across both platforms.
• Optimized SQL queries, Delta tables, and database objects using techniques such as partitioning, V-Order/OPTIMIZE, clustering, and query tuning to reduce processing time for regulatory reporting.
• Supported end-to-end data integration by validating field mappings, implementing derived columns, and ensuring compliance with regulatory reporting standards.
• Worked extensively with Snowflake objects (Views, Tables, CTEs, Temporary Tables, Stored SQL logic) and Fabric components (Lakehouse, Warehouse, Shortcuts, Pipelines, Notebooks, Semantic Models) to support enterprise reporting solutions.
• Maintained technical documentation for data mappings, transformation rules, SQL/pipeline logic, and end-to-end data lineage to support enhancements and production support.
• Performed UAT and production data validation by comparing source and target outputs, ensuring accurate and auditable regulatory reporting.
• Worked in an Agile environment using Rally to manage sprint backlogs, update daily task status, track user stories, and monitor progress of data engineering activities.
• Partnered with cross-functional teams to troubleshoot production issues, perform root cause analysis, and implement data fixes with minimal business impact.

PROJECT :- BlueYonder / JDA Supply Chain

• Increased global supply chain efficiency and development by leading cross-functional teams and enabling supplier integration and management technology tools, upgrades.
• Reduced inventory levels and improved supply chain visibility using strategic initiatives.
• Created and implemented comprehensive supply chain management strategies.
• BlueYonder customer utilizing the Manufacturing and Planning Suite products across the globe using BY ESP, BY SNOP, BY IO.
• Led a cross-functional team to architect and deploy a serverless application using AWS Lambda and API Gateway, reducing operational costs by 30% and improving scalability.
• Implemented a comprehensive CI/CD pipeline using AWS CodePipeline and CodeBuild, decreasing deployment time by 50% and enhancing release reliability.
• Identify assumptions, risk, constraints and dependencies Outline the various capabilities of the testing process
• Defined and documented the testing strategy for Snowflake data pipelines and reporting views, describing the tasks of each testing capability — unit testing of SQL logic, source-to-target data validation, reconciliation testing, integration/system testing, regression testing, and UAT for regulatory reporting datasets.
• Established Entry and Exit criteria for each testing phase — Snowflake objects (views, tables, SQL scripts) deployed to the test database/schema, STTM baselined and approved, test data loaded into Snowflake stage/raw layers, zero open critical defects, and source-to-target reconciliation variance within agreed tolerance before sign-off.
• Outlined roles and responsibilities across the testing process — data engineers for SQL/view fixes and re-runs, test lead for cycle execution and defect triage, business/regulatory SMEs for rule validation and UAT approval, and the Power BI team for downstream report validation on Snowflake views.

• Developed and modified triggers, packages, functions and stored procedures for data conversions and PL/SQL procedures to create database objects dynamically based on user inputs.
• Strong, demonstrable debugging skills using tools from a variety of Python IDES (PyCharm, Eclipse)
• Core Python Expertise.
• Created and modified SQL PLus, PL/SQL and SQL Loader scripts for data conversions.
• Automatedized
  collecting data using SQL, reaching over a 35% system’s response time boost.
• Build appropriate and useful reporting deliverables Analyze existing SQL queries for performance improvements.
• Maintain and enhance the source code and process flow for the department’s SAS production environment
• Ensured smooth communication between the development team and the client, focusing on a correct transition of the requirements and specifications.
  
• Explored different implementations in hadoop environment for data extraction and summarization by using packages like Hive, Pig.
• Collaborated with team members to achieve target results.
• Demonstrated respect, friendliness and willingness to help wherever needed.

Business Analyst

• Research required data.
• Build appropriate and useful reporting deliverables Analyze existing SQL queries for performance improvements.
• Driven healthcare professional with more than 5 years of experience in medical administration and management. Highly knowledgeable in managing patient records, medical billing, and hospital expenses.
• Suggest new queries

Reporting Analyst

• Maintain databases and perform updates as necessary to ensure accuracy
• Create business reports that provide insight into key data points
• Checking and cleaning data, taking special care toreplace erroneous values with correct figures.