Senior Data Engineer

• 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