Designs and maintains SQL Server star-schema data warehouses, SSIS ETL pipelines, and SSAS semantic models for financial reporting. Integrates data models with Power BI, implements SCD logic, row-level security, KPI calculations, and data quality controls. Produces technical documentation covering data models, ETL, lineage, security, and operating procedures. Requires strong T-SQL, data warehousing, performance tuning, and Microsoft BI experience, with finance-domain knowledge and stakeholder communication skills preferred.
Location: Mumbai
Experience: 2–4Years
Employment Type: Full-time
Position Overview:
We are seeking a hands-on Sr. Database Engineer with deep expertise in the Microsoft data and BI ecosystem to join our team for a strategic finance data warehousing and reporting engagement. The role focuses on designing and building a star-schema data warehouse on Microsoft SQL Server, developing high-performance ETL pipelines using SSIS, constructing SSAS semantic models, and integrating these with Power BI for enterprise-grade financial reporting.
The ideal candidate has worked on similar on-premises Microsoft BI implementations and is comfortable owning the full data pipeline from source extraction to semantic layer delivery.
Key Responsibilities:
- Design, build, and maintain a star-schema data warehouse on SQL Server with fact and dimension tables for each finance domain.
- Implement SCD Type 1 and Type 2 dimension maintenance logic with a master data change notification mechanism.
- Build and maintain SSAS tabular/multidimensional models as the centralized semantic layer with KPI calculations and business rules.
- Integrate the semantic layer with Power BI datasets; support Power BI report development team with data model optimization.
- Implement row-level security (RLS) aligned to report recipient groups; maintain the role-entity mapping table independently.
- Embed data quality measures in the data warehouse: uniqueness, completeness, validity, and integrity checks.
- Create comprehensive technical documentation: data model, ETL flows, data lineage, KPI calculations, RLS design, and operating manuals.
Required Qualifications & Experience:
- 2–4 years of hands-on experience with Microsoft SQL Server including database design, performance tuning, and administration.
- Strong hands-on experience developing and managing SSIS packages for complex ETL pipelines – scheduling, error handling, logging, incremental loads.
- Proven experience building SSAS tabular or multidimensional models; semantic layer design with centralized KPI definitions and business rules.
- Deep expertise in star/snowflake schema data warehouse design with fact and dimension tables, SCD Type 1/2 implementations.
- Experience integrating SSAS/SQL Server data models with Power BI; and Power BI dataset design.
- Strong proficiency in advanced T-SQL – stored procedures, views, CTEs, window functions, query performance tuning.
- Experience implementing row-level security (RLS) in SQL Server and/or Power BI.
- Experience with data quality frameworks – building validation checks, reconciliation logic, and data integrity monitoring.
Preferred / Bonus Skills:
- Experience with Oracle Fusion ERP data extraction
- Familiarity with Zebra BI visuals within Power BI
- Experience with SharePoint list-based collaboration and commenting integrations.
- Awareness of Power BI Service application deployment, bookmarks, drill-down/drill-up navigation, and guided navigation patterns.
- Finance domain knowledge – General Ledger, AP, AR, Treasury, Revenue reporting cycles.
- Microsoft certifications (DP-500, PL-300, or equivalent).
Soft Skills & Expectations:
- Excellent communication skills – able to engage with finance stakeholders and translate business requirements into technical data models.
- Strong documentation skills – ability to produce clear technical documentation, operating manuals, and data dictionaries.
- Ownership mindset – comfortable taking end-to-end responsibility for data pipeline delivery.
- Comfortable working in a rapid phased delivery engagement
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