SSIS, SSAS, SSRS, MSBI

Primary skills:Technology->Business Intelligence - Analytics->MSBI (SSAS) Technology->Business Intelligence - Reporting->MSBI (SSRS) Technology->SQL SSIS->SQL Server

Key Responsibilities:

• Lead end-to-end development and support of MSBI solutions using SSIS, SSAS, and SSRS across multiple subject areas.
• Design, develop, and optimize SSIS ETL packages including data extraction, transformation, loading, scheduling, and error handling.
• Build and maintain SSAS tabular/multidimensional models, measures, KPIs, hierarchies, and partitions aligned to business reporting needs.
• Develop SSRS reports, datasets, and subscriptions; ensure report accuracy, usability, and performance.
• Write and tune complex SQL queries, stored procedures, and views to support ETL and reporting workloads.
• Perform performance tuning for ETL, cube/model processing, and reporting; analyze bottlenecks and implement improvements.
• Drive requirement discussions with stakeholders, convert needs into technical designs, and ensure timely, quality delivery.
• Implement data validation, reconciliation checks, and monitoring to improve reliability and data quality.
• Provide technical guidance, code reviews, and mentoring to team members; promote best practices and standards.
• Support production deployments, troubleshooting, and root-cause analysis with clear documentation and communication. Minimum Qualifications:
• BTECH, MTECH, MCA, or MSC.
• 5–8 years of experience delivering BI solutions using SSIS, SSAS, SSRS, and MSBI.
• Strong hands-on expertise in SQL including query writing, optimization, and database objects (views, stored procedures).
• Proven experience building ETL workflows in SSIS with robust logging, error handling, and scheduling.
• Experience developing SSAS models and SSRS reports with a focus on performance and correctness.
• Working knowledge of Python for data processing, automation, or integration tasks supporting BI delivery. Preferred Qualifications:
• Experience designing dimensional data models (star/snowflake) and applying BI best practices for analytics-ready datasets.
• Strong troubleshooting skills across ETL, semantic models, and reporting layers with a structured approach to root-cause analysis.
• Experience with Python libraries for data handling and automation (e.g., Pandas) to complement BI workflows.
• Exposure to version control and release practices for BI assets; ability to maintain clean, reusable, well-documented code.
• Demonstrated leadership in coordinating deliveries, improving team standards, and collaborating effectively with business stakeholders.