Data Modeling:

Design and develop data models for Azure-based data solutions, including data lakes, data warehouses, and data pipelines.

Data Architecture:

Collaborate with data architects and engineers to define data architecture patterns and implement Azure best practices.

Data Ingestion:

Create and implement data ingestion strategies to ensure efficient collection, processing, and storage of data.

ETL Development:

Build and optimize ETL processes using tools like Azure Data Factory and Databricks to support business needs.

Data Quality:

Implement data validation and cleansing routines to maintain data accuracy and integrity.

Data Governance:

Ensure data solutions adhere to governance and security policies, including access controls and encryption standards.

Performance Optimization:

Monitor and optimize performance of data models, queries, and processing workflows.

Documentation:

Maintain detailed documentation for data models, schemas, pipelines, and flow diagrams.

Cross-Functional Collaboration:

Work closely with data engineers, scientists, analysts, and business stakeholders to understand requirements and deliver solutions.

Bachelor's degree in Computer Science, Information Technology, or related field
3–5 years of experience in data engineering, with a focus on Azure platforms
Proficiency in data modeling tools and query languages (e.g., SQL)
Strong hands-on experience with Azure Data Factory, Azure Databricks, and Power BI
Solid understanding of data lakes, data warehouses, and data integration
Knowledge of Azure Synapse, Data Lake Storage, and SQL Data Warehouse
Strong problem-solving and analytical thinking abilities
Excellent communication and team collaboration skills

Azure Data Engineer

Dot Net Core Developer with Angular