Role Overview :

We are seeking an experienced Data Engineer to design, develop, and maintain enterprise-scale Data Warehouse solutions. The ideal candidate will be responsible for building robust data pipelines, optimizing data models, managing large-scale data platforms, and ensuring high-quality, trusted data assets that support analytics, AI, and business decision-making.

Key Responsibilities :

Data Warehouse Development :

- Design, develop, and maintain enterprise Data Warehouse solutions.

- Build and manage dimensional data models including Fact and Dimension tables.

- Implement Star Schema designs.

- Define and maintain enterprise data architecture standards.

Data Engineering & ETL :

- Design and build ETL/ELT pipelines for structured and unstructured data sources.

- Develop scalable data ingestion, transformation, and integration frameworks.

- Ensure data quality, integrity, reconciliation, and validation.

- Implement automated data processing and orchestration workflows.

Tech Stack :

- Data Platforms : Azure Synapse Analytics, Azure Data Factory, Databricks, Azure Data Lake Storage (ADLS Gen2)

- Programming Languages : Python, SQL, PySpark

- Data Orchestration : Apache Airflow, Azure Data Factory Pipelines

Desirable AI Capabilities :

- Experience building data platforms for Generative AI and Machine Learning workloads.

- Exposure to Vector Databases, Embeddings, and RAG techniques.

- Familiarity with LLMs such as Azure OpenAI, Claude, or Gemini.