Design and implement data pipelines using Azure Data Factory to ingest, transform, and load data from various sources into Azure data storage solutions.

Develop and maintain data models and database schemas in Azure Synapse Analytics or Azure SQL Database to support business intelligence and analytics requirements.

Implement data governance and security policies to ensure data quality, compliance, and protection of sensitive information in Azure data environments.

Optimize data storage and processing performance by tuning queries, indexing strategies, and data partitioning techniques in Azure data platforms.

Monitor and troubleshoot data pipeline performance, identify bottlenecks, and implement solutions to improve data processing efficiency and reliability in Azure.

Collaborate with data scientists and business analysts to understand data requirements and design data solutions that meet their analytical needs using Azure services.

Automate data integration and ETL processes using Azure Logic Apps or Azure Functions to streamline data workflows and reduce manual intervention.

Implement data warehousing solutions using Azure Data Lake Storage and Azure Databricks to enable large-scale data processing and analytics.

Develop and maintain documentation for data pipelines, data models, and data governance policies to ensure knowledge sharing and compliance in Azure.

Stay up-to-date with the latest Azure data services and technologies, and evaluate their potential to improve data engineering practices and solutions.

Participate in code reviews and testing to ensure the quality and reliability of data engineering solutions in Azure environments.

Manage and maintain Azure Data Lake Storage Gen2 for storing structured and unstructured data, ensuring optimal performance and cost-effectiveness.

Architect robust data pipelines for efficient data ingestion, transformation, and loading into Azure data services.

Utilize Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure Databricks for data processing.

Design and implement data models optimized for performance, scalability, and business requirements in Azure environments.

Develop and maintain ETL (Extract, Transform, Load) processes using Azure Data Factory or custom scripting.

Implement data security measures, including encryption, access control, and data masking, within Azure data solutions.

Optimize query performance and overall system efficiency in Azure Synapse Analytics and other data services.

Establish and enforce data governance policies to ensure data quality, compliance, and consistency across Azure data assets.

Implement real-time data processing solutions using Azure Stream Analytics or Azure Event Hubs.

Integrate data from various sources, including on-premises systems and cloud applications, into Azure data platforms.

Automate data engineering tasks, such as data validation, monitoring, and deployment, using Azure DevOps.

Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver data solutions.

Create and maintain comprehensive documentation for data pipelines, data models, and data engineering processes.