Principal Data Engineer

As Principal Data Engineer on our Data Service Team, your purpose is to drive tangible business outcome by providing solution, development, and optimization of scalable and high-performance data architecture. You will be pivotal in empowering business users with timely, reliable, and actionable data, directly impacting and improving organization decision-marking, operational efficiency, and customer experience. Your ultimate goal is to enable data-driven initiatives and advanced analytics that are fundamental to the company's strategic growth.

Main accountabilities:

• Deliver reliable and scalable data pipeline by designing, building and managing data pipelines that ensure timely, reliable, and high-quality data delivery, enabling the business to make data-driven decisions efficiently
• Facilitate business outcome through cross-functional collaboration by working closely with market business stakeholders, regional teams to understand requirements and data solutions that directly impact to business outcomes and customer experiences
• Ensure data quality and integrity by proposing and implementing data quality rules to maintain accuracy, consistency, and trustworthiness of data used in reporting, analytics and operational systems
• Enable cost-effective and high-performing data infrastructure by continuously optimizing data architectures and workflows to reduce processing costs, improving system performance, and supporting scaling of data solutions
• Drive innovation in data engineering practices by introducing and applying modern engineering tools, techniques, and best practices to enhance team's productivities
• Other assignments

Technical skills:

• Strong experience in AWS data stack such as AWS Glue Job (PySpark), Glue Data Catalogs, Glue Data Quality, Lake Information, Lambda, S3, IAM
• Strong experience in application data architecture, data design patterns such as data lake, data warehouse, and data marts for life insurance
• Strong knowledge of SQL and NoSQL such as spark query, Athena, Redshift, PostgreSQL, SQL Server, DynamoDB.
• Good knowledge in ETL batch, micro batch workflow by using SSIS
• Good knowledge of life cycle of application developments.
• Good knowledge of DataOps tools and practices (source control, build, CI…).

Soft skills:

• Effective project communication
• Collaborative Problem-Solving session
• Critical evaluation of Data Architecture
• Embracing change and learning
• Cross-function team projects

Problem solving:

• The Principal Data Engineer is expected to proactively identify root causes of recurring or potential data issues, ranging from pipeline reliability, data quality, system performance, scalability, and cost optimization
• The role demands strong analytical and problem-solving skills, with a proven ability to architect and implement effective, scalable, and long-lasting solutions that directly support critical business decisions and operational excellence. This role requires solving a wide range of complex and interdependent problems across data architecture, engineering workflows, and business data needs

Education:

University or College degree in IT or equivalent.

Experience:

At least 7 years of experience in Data development.

Communication scope:

The role requires strong communication skills to clearly articulate complex technical concepts to both technical and non-technical audiences

• Internal Teams: Regularly collaborate with Data Engineers, Software Engineers, Data Analysis, Reporters on both local and regional to design and deliver scalable data solutions.
• Cross-function collaboration: Regularly engages with Business users from other departments to ensure data solutions adhere to regulatory requirements, data governance policies, and industry best practices