Experience Range : 6 to 9 years
Minimum Qualifications :
- 6+ years of SQL Server development experience ( SQL Server 2012 and later)
- 6+ years working with ETL / ELT tools such as SSIS, Informatica
- 6+ years optimizing SQL queries and SSIS packages for performance
- 6+ years working with data warehousing concepts and dimensional modeling (e.g., Star Schema)
- 6+ years in data modeling and database design
- 3+ years developing SSAS Tabular and / or Multidimensional models, with MDX
- 3+ years experience building dashboards using Power BI and DAX (or equivalent)
- 4+ years working with XML, JSON, PowerShell, and REST APIs
- 4+ years of Azure data platform implementation experience
- Strong T-SQL skills for data manipulation and stored procedure development
- Experience with both on-premises and cloud BI environments (e.g., Azure SQL DB, Azure Data Factory, Power BI Service)
- Good understanding of data quality, validation techniques, and governance practices
- 3+ years using Agile tools like Jira, Bitbucket, Confluence
- 3+ years working with ticketing tools like ServiceNow, JIRA, or Quality Center
- Experience with SharePoint for document collaboration
- High proficiency with Microsoft Office tools
- Strong communication skills across technical and business teams
- Ability to work independently and collaboratively in distributed teams
- Flexible and adaptable to evolving project deliverables and business priorities
Principal Duties and Responsibilities :
Design, develop, and maintain scalable ETL pipelines using SSIS and / or Azure Data FactoryDevelop complex SQL queries, stored procedures , views, and user-defined functionsBuild and maintain SSAS models (Tabular / Multidimensional) for analytical consumptionCreate interactive dashboards and reports using Power BICollaborate with business analysts and data stakeholders to gather and translate requirements into data solutionsParticipate in all phases of the BI solution lifecycle, from design and development to testing and deploymentMonitor and troubleshoot BI and ETL processes; identify performance bottlenecks and implement solutionsFollow best practices in development, code reviews, testing, and documentationStay current with new tools and technologies in the data ecosystemAdhere to enterprise data governance, privacy, and security standards