Senior Data Engineer

Key Responsibilities :

• Collaborate with CCH architects across different IT (DTPS) teams and with cross-functional teams to gather requirements, define technical specifications, and provide architectural guidance for Azure projects. Contribute and align on the strategy, design and implementation of the end2end data journey to expose analytics insights for consumption by different reporting layers.
• Ability to load data from Azure Data Sources (Azure SQL Databricks Warehouse / Synapse), visualize data, setup data refresh, analyze and write queries in SQL.
• Develop and implement data governance and data quality frameworks to ensure the integrity and accuracy of data;
• Design, develop, implement and optimize data pipelines for scalability, performance, security and cost efficiency. Optimize data storage, retrieval, and processing techniques to achieve high performance and cost efficiency.
• Implement security and access control measures to protect sensitive data within Azure environments.
• Perform data profiling, analysis, and validation to identify and address data quality issues.
• Develop and maintain documentation for data solutions, including data models, data flows, and technical specifications.
• Stay up to date with the latest Azure data services, tools, and best practices, and provide recommendations for their adoption.
• Lead and guide Azure developers and data engineers from vendors, providing guidance and support in Azure data engineering techniques and methodologies and ensuring development as per CCH standards and guidelines.
• Ability to understand business requirements and convert into clearly documented technical requirements (dimensions, KBIs, data structure, data granularity, target users), following the agreed guidelines, standards and rules.
• Collaborate with DevOps teams to implement continuous integration and delivery pipelines for Azure-based applications.
• Collaborate with and support Power BI developers to test different approaches for data connections and data transfers to Power BI, to identify the optimal approach per use case considering data volume, Power BI performance, as well as data quality and security considerations.

Requirements