Sr. Database Engineer – Microsoft BI Stack (SSIS/SSAS)

OneTure Technologies Private Limited; Navi Mumbai; On-site; INR 1,100,000 - 1,800,000; Full time

Job summary

OneTure Technologies Private Limited is seeking a hands-on Sr. Database Engineer with deep expertise in the Microsoft data and BI ecosystem to join a strategic finance data warehousing and reporting engagement.

The role designs a star-schema data warehouse on SQL Server, develops ETL pipelines with SSIS, builds SSAS models, and integrates them with Power BI for enterprise financial reporting. The ideal candidate has delivered on-premises Microsoft BI implementations and owns the full data

Qualifications

• 2–4 years 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.
• 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; Power BI dataset design.
• Strong proficiency in advanced T-SQL – stored procedures, views, CTEs, window functions, performance tuning.
• Experience implementing row-level security (RLS) in SQL Server and/or Power BI.
• Experience with data quality frameworks – validation checks, reconciliation logic, data integrity monitoring.

Responsibilities

• Design, build, and maintain a star-schema data warehouse on SQL Server with fact and dimension tables for finance domains.
• Implement SCD Type 1 and Type 2 dimension maintenance logic with a master data change notification mechanism.
• Build and maintain SSAS tabular or 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.

Skills

SQL Server

SSIS

SSAS

Power BI

T-SQL

Data warehouse design

RLS

ETL pipelines

Data modeling

Performance tuning

Tools

SQL Server

SSIS

SSAS

Power BI

Oracle Fusion ERP data extraction

Job description

2-4 years

Full-Time

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).
• 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