Praveen Reddy

Software Engineer 1

MAQ Software

Aug 2023 - Present

Owned the design and development of Power BI dashboards and reports for business stakeholders, using DAX measures, visuals, bookmarks, and Power Query (M) transformations. Created scalable dimensional and semantic data models using Power BI, SSAS Tabular Model, Tabular Editor, and C# (Tabular Object Model), including relationships and Row-Level Security (RLS). Led implementation of Direct Lake semantic models using a star-schema approach, improving report performance and scalability for KPI dashboards and executive-level reporting. Managed Power BI workspaces and scheduled refresh configurations to support reliable, self-service reporting for business teams. Designed, developed, and maintained scalable ETL pipelines in Microsoft Fabric and Azure Data Factory, moving and transforming data from SQL Server and SAP into optimized Delta tables in ADLS and Fabric OneLake. Used Databricks, PySpark, and SQL to clean, transform, and integrate large, multi-source datasets into reliable, analysis-ready tables, including Microsoft Fabric's sempy packages for semantic-model ETL. Wrote and optimized complex SQL queries using joins, CTEs, and window functions, along with stored procedures, functions, and triggers in Microsoft SQL Server, applying indexing and partitioning strategies to improve performance. Performed ad-hoc analysis and data segmentation using SQL and Power BI to identify trends, track key metrics over time, and uncover opportunities for business improvement. Defined and tracked KPIs and performance metrics for business stakeholders, translating business requirements into dashboard specifications and data models. Communicated findings and recommendations clearly to both technical and non-technical stakeholders through dashboards, reports, and visualizations. Built automated data validation and quality-check pipelines to ensure data accuracy, integrity, and consistency, catching inconsistencies before they reached downstream reports. Contributed to data governance by standardizing semantic models, metadata, and naming conventions, and documented database schemas, pipelines, and query logic for team reference. Automated recurring data-processing and reporting workflows using a C# Azure Function App and Power Automate, incorporating Application Insights logging to reduce manual intervention and improve reliability. Mentored and guided junior team members on Power BI development, SQL best practices, and reporting standards, and partnered with SAP and finance stakeholders to gather requirements and deliver decision-ready reporting. Applied AI-assisted development tools, including GitHub Copilot and MCP tooling, to accelerate development and automate repetitive tasks while safeguarding confidential data.