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regional senior data engineer

A MNC F&B company

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.

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 need