regional senior data engineer

概覽

公司資訊

所需技能

• Bachelor’s degree holder in Computer Science, Data Science, Statistics, Mathematics or equivalent
• Minimum 5 years of experience in data engineering or a similar role.
• Strong proven expertise in Azure Synapse Analytics, Databricks, and other Azure cloud technologies.
• Proficiency in Python, PySpark, and other relevant programming languages for ETL automation.
• Experience in designing and implementing data models, including star schemas and other dimensional models.
• Experience in Data Management tools such as Data Lake, BI, ETL, Dashboards, Balanced Scorecards, etc.
• Excellent communication and presentation skills, to communicate complex analytical and technical content clearly and effectively.
• Demonstrated ability to work with large, complex datasets and build scalable data solutions.
• Track record of forming strong partnerships with cross-functional teams.
• Experience with data visualization tools and an understanding of how data engineering supports data analytics.

工作職責

• Design, develop, and maintain robust data pipelines and ETL processes to support data integration and transformation across multiple data sources.
• Design analytical solutions for strategic business problems through engagement and research.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and translate them into technical solutions in meeting milestones, timelines, and deliverables for projects.
• Implement and optimize data models, including star schemas, to facilitate efficient data querying and analysis.
• Leverage Azure Synapse Analytics, Databricks, and other Azure services to build scalable data infrastructure.
• Ensure data quality and consistency across all layers of the data lakehouse (bronze, silver, and gold layers).
• Automate ETL processes using SQL, Python, PySpark, or other relevant technologies to streamline data ingestion and transformation.
• Monitor and maintain the performance, security, and reliability of data systems.
• Provide technical leadership and guidance on best practices for data engineering within the organization.
• Document data pipelines, processes, and architecture to ensure transparency and knowledge sharing.
• Work either individually or in project teams as a subject matter expert to deliver business needs.
• A key contributor to the development of organization data infrastructure and collaborate closely with vendor’s data engineers on a day-to-day basis to ensure development drives business outcomes.
• Create impeccable and user-friendly documentation for data sources and data dictionaries across the company.
• Establish a clear Business Glossary to keep everyone on the same page by defining common terminology and interpretation of the same data.
• Validate data structure in the Data Management Platform, refine logic and data transformation, and build aggregation tables to provide seamless reporting and data access across the business.
• Improve data maturity with high data quality, reliability, and visibility of business insights in a consistent manner and enable the business team to identify opportunities and threats for the company.

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