Data Engineer (Hybrid Role)

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• 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.

New data integration and data infrastructure

• 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

EDUCATION/QUALIFICATION/EXPERIENCE

• 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.

KNOWLEDGE, SKILLS & ABILITIES REQUIRED

• Highly proficient in data analysis and data mining skills (such as Python, Scala, R, T-SQL, MDX, DAX, etc.)
• Strong analytical skills with the ability to translate business needs into technical solutions.
• In-depth knowledge and understanding of data relationships and able to comprehend the data.
• Understand the reporting and business intelligence best practices.
• Ability to synthesize information from various sources to Data Management Platform to create a single and actionable point of view and direction for BI reporting requirements.
• Highly resourceful, with strong research skills and a working knowledge of digital marketing analytics.
• Possess a strong ability to query and use large, robust data sets across the latest Delta Lake and Databrick platforms.
• Strong understanding of data governance, security, and compliance best practices.
• Ability to manage multiple priorities and projects simultaneously.

OTHERS

• Fluent communication in English and interpersonal skills, both verbal and written.
• Meticulous and good team player who can work with various levels of stakeholders from different cultures and locations.
• Ability to work in a flexible, dynamic, and fast-paced