Retail Data Domain & System Exploration
Explore, profile, and understand data structures across various retail source systems (ERP, CRM, Supply Chain, E-Commerce, Inventory Management, etc.).
Data Ingestion & Pipeline Development (ETL/ELT)
Build and maintain high-performance pipelines using SSIS and n8n to extract data from diverse source systems into the Data Warehouse.
Advanced SQL & Query Optimization
Write, tune, and optimize highly complex SQL queries, stored procedures, and window functions to handle large-scale data transformation and complex business logic efficiently.
Data Warehouse Management
Maintain and manage enterprise Data Warehouse architectures.
Data Exploration & Cleansing
Explore, profile, and clean complex datasets across legacy and modern business systems to ensure high data accuracy and readiness for analytical consumption.
Semantic Layer & SSAS Management
Build and optimize SSAS Tabular Models, managing data partitions, memory processing, and Row-Level Security (RLS).
Data Technical Innovation
Drive technical innovation through AI integration and advanced data capabilities.

Experience: 2–3 years of hands-on experience in Data Engineering, ETL Development, or Data Warehousing.
Domain Knowledge: Strong familiarity with retail business domains (e.g., POS data, omnichannel sales, inventory movement, store operations, product hierarchies, promotions).
Mandatory Core Skills:
SQL: Expert-level querying, indexing, and performance tuning.
Microsoft BI Stack: High proficiency in SSIS and SSAS (Tabular Models).
ETL & Automation: Experience with n8n or similar orchestration tools; comfortable writing Python for data manipulation and task automation.
Architecture & AI: solid understanding of Data Warehouse design principles and AI knowledge.
Security & Governance: Clear understanding of data governance and Row-Level Security (RLS).
Execution & Soft Skills: Strong commitment to project timelines, delivering quality data solutions under pressure in fast-paced environments.

Data Engineer

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