Manjushree Mutta

Projects: Data Migration, Transformation, and Analytics Enablement.

• Led Azure cloud migration projects involving complex source-to-target data mappings, and large-scale legacy data modernization.
• Designed data lake zone architecture (raw, curated, refined), and developed ingestion pipelines using Azure Data Factory (ADF) for seamless data flow.
• Developed and maintained optimized PySpark notebooks in Azure Databricks for data cleansing, transformation, aggregation, and validation.
• Applied performance tuning techniques such as caching, broadcast joins, and partitioning, reducing job runtimes by up to 40%.
• Defined and enforced semantic layer standards in collaboration with data architects to ensure cross-domain data consistency and reuse.
• Implemented CI/CD pipelines using Azure DevOps for ADF, Databricks, and data lake deployments, streamlining release management, and reducing manual interventions.
• Automated pipeline monitoring and alerting to proactively detect and respond to failures, improving data reliability and SLA adherence.
• Mentored and guided a team of junior engineers and analysts, promoting clean code practices, code reviews, and scalable design patterns.

Project: Salesforce Data Integration and KPI Dashboard.

• Served as a Data Analyst, leading the effort to map and align key data attributes across Salesforce, GSAP, and MDM systems.
• Delivered a robust KPI dashboard in Einstein Analytics, enabling leadership visibility into operational and sales metrics.
• Facilitated cross-functional data validation workshops to ensure reliable data exchange across systems.
• Maintained documentation of all the processes related to Data Analysis.
• Worked with internal teams to understand business needs and changing strategies.

Projects: Business Intelligence, Analytics, and Reporting.

• Led a team of developers in building modular, high-performance SQL-based reporting layers across multiple data sources.
• Developed complex SQL queries using joins, CTEs, window functions, and CASE logic to enable deep insights for finance and sales analytics.
• Designed and governed star schema and snowflake data models to support self-service BI.
• Partnered with business leads to define KPIs and reporting requirements, aligned with evolving business strategies.
• Spearheaded the performance optimization of analytics queries, improving response time on high-volume datasets by 40%.