Manasa Reddy Palem

Designed and maintained end-to-end analytical data solutions using Microsoft Fabric, Snowflake, and SQL Server, building scalable data models and curated layers for enterprise reporting and advanced analytics.

Developed and optimized complex SQL queries (CTEs, window functions, stored procedures, views) to transform high-volume transactional datasets into analytics-ready tables for Power BI dashboards.

Built and managed ETL/ELT pipelines using Microsoft Fabric (Dataflows, Lakehouse), Azure Data Factory, Databricks, and Snowflake, integrating data from multiple enterprise systems into centralized data platforms.

Designed interactive Power BI (Desktop, Service, Apps) dashboards leveraging DAX and Power Query to deliver KPI reporting, financial analysis, lifecycle tracking, and forecasting insights.

Partnered with business stakeholders to translate ambiguous requirements into technical specifications, documenting user stories and managing sprint deliverables through Jira in Agile environments.

Performed data profiling, validation, and quality assessments to ensure completeness, accuracy, and governance compliance across reporting and AI-ready datasets.

Implemented production-grade reporting solutions including scheduled refreshes, semantic models, performance optimization, and Row-Level Security (RLS) within Power BI Service.

Collaborated closely with data engineering and analytics teams to enhance pipeline performance, optimize warehouse queries in Snowflake, and support scalable cloud data architectures.

Supported analytics and AI initiatives by preparing standardized, well-documented datasets aligned with enterprise data governance and metadata management standards.

Analyzed data trends to support decision-making processes.

Created reports to communicate findings to stakeholders effectively.

Assisted in data collection and validation for accuracy and completeness.

Developed dashboards using data visualization tools for enhanced insights.

Contributed to process improvement initiatives through data-driven recommendations.

Used statistical methods to analyze data and generate useful business reports.

Collaborated with cross-functional teams to ensure data integrity and accuracy, resulting in better-informed decisions.

Integrated multiple sources of disparate data into cohesive datasets using ETL processes, improving overall analytic capabilities.

Provided actionable insights through comprehensive reports and dashboards, supporting strategic initiatives.

Improved data visualization techniques, making insights more accessible to non-technical stakeholders.

Automated routine data analysis tasks, freeing up time for more complex analysis.

Enabled more personalized customer experiences by analyzing behavior patterns and preferences.

Developed and maintained data pipelines for seamless flow of information, ensuring timely availability for decision-making.

Updated and developed scripts and queries to extract and analyze data from multiple sources.

Provided technical support for troubleshooting analytics and reporting issues.

Collected, cleaned, and analyzed data from SQL Server, Excel, and enterprise systems to support business reporting, KPI tracking, and operational decision-making.

Developed SQL queries using joins, aggregations, CTEs, and views to transform raw data into structured, analytics-ready datasets.

Created interactive dashboards and reports using Power BI and Excel, enabling stakeholders to monitor trends, performance metrics, and business outcomes.

Performed data validation, profiling, and quality checks to ensure accuracy, completeness, and consistency across reporting datasets.

Collaborated with business stakeholders to gather requirements, translate business needs into technical solutions, and deliver actionable insights.

Automated recurring reporting workflows using Power BI scheduled refreshes, Power Query, and reusable SQL scripts, reducing manual reporting efforts.

Optimized SQL queries, data models, and reporting processes to improve performance, scalability, and report efficiency.

Migrated and integrated datasets from on-premise systems into cloud platforms such as Microsoft Fabric, Azure SQL, and Snowflake to support scalable analytics.

Built and maintained cloud-based data models, semantic layers, and curated datasets to enable enterprise reporting and self-service analytics.

Developed and managed ETL/ELT pipelines using Microsoft Fabric Dataflows, Azure Data Factory, or similar tools to automate data ingestion and transformation.

Implemented secure and governed reporting solutions using Power BI Service, including scheduled refreshes, access controls, and Row-Level Security (RLS).

Supported analytics automation initiatives by creating standardized, reusable datasets and collaborating with data engineering teams to improve pipeline performance and data reliability.