Job Description

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.