Role : Data Engineer
Location : San Jose CA ( Onsite)
Experience: 10 Years
Key Skills : Power BI ETL Azure Python
We are seeking a skilled data expert to transform complex raw data into actionable business insights. This role focuses on designing building and maintaining scalable data pipelines using Azure Fabric and SSIS ensuring our Sales (SFDC) Finance (NAV/BC) and Product (MSC) data is unified and ready for advanced reporting in Power BI.
Skill Set & Expertise Requirements
Data Engineering: SSIS Azure Data Factory Azure Fabric (Pipelines Medallion Architecture)
Design end-to-end Medallion Architecture manage complex data migrations
Languages: Advanced SQL Python (Pandas/NumPy)
Proficiency in performance tuning indexing and complex Python-based data manipulation
Big Data: Apache Spark Azure Fabric Notebooks
Experience in distributed processing and PySpark-based notebook development.
Data Modelling: Kimball Methodology (Facts/Dimensions)
Deep understanding of dimensional modeling for BI performance.
BI & Reporting: Power BI DAX Power Query
Ability to create complex DAX measures and professional-grade storytelling dashboards.
Platforms: Gainsight SFDC NAV/BC Jira
Hands-on experience integrating these diverse data sources into a central warehouse.
Tools: Git (Version Control) MSPO
Essential for collaborative development and environment management.
Key Responsibilities
Data Engineering & ETL
Pipeline Development: Design and deploy end-to-end ETL/ELT processes using Azure Data Factory and Azure Fabric (Notebooks & Pipelines).
Architecture Management: Implement and maintain Medallion Architecture (Bronze/Silver/Gold) and Kimball Methodology (Star Schemas) to ensure high-performing Data Warehousing.
Legacy Maintenance: Manage existing SSIS packages to ensure seamless data flow from on-prem and cloud sources.
Reporting & Analytics
Dashboarding: Build sophisticated Power BI reports using Power Query for data transformation and DAX for complex calculations.
Platform Management: Administer the Power BI Service and manage data integration with Gainsight to drive Customer Success initiatives.
Source Integration: Extract and sync data from diverse sources including SFDC NAV/BC Jira and product usage data (MSC).
Database & Collaboration
SQL Optimization: Write and optimize complex Stored Procedures Views and Indexes for efficient data retrieval.
Version Control: Maintain codebase integrity using Git for version control and collaborative development.
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