Key Responsibilities:
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.
Qualifications:
- Bachelor's degree in Computer Science, Information Technology, or related field
- 35 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
