Senior Data Engineer

Introduction

DigiEx Group is a global technology partner specializing in Innovation Software Development, AI-powered solutions, Tech Talent services, and Digital Transformation. Headquartered in Vietnam, DigiEx helps startups and enterprises worldwide build scalable digital products and high-performing engineering teams.

At DigiEx, we embrace an AI-first engineering culture, empowering every team member to leverage AI technologies to build smarter software, improve productivity, and continuously innovate.

Key Responsibilities

• Build, maintain, and optimize data pipelines for data ingestion, transformation, and loading across analytical and operational data sources.
• Develop and optimize complex SQL transformations across large-scale datasets, ensuring performance, accuracy, and data consistency.
• Design and maintain tables, views, and data models that support downstream reporting, analytics, and application workflows.
• Own data quality and pipeline monitoring, proactively identifying and resolving failures before they impact client dashboards or operational systems.
• Support custom and non-standard data requirements, including specialized datasets, one-off data extracts, ad-hoc analytical builds, and custom data processing workflows.
• Document pipeline architecture and data model decisions clearly, enabling QA and delivery teams to understand, validate, and verify implementations.
• Work within established CI/CD processes and quality gates, ensuring pipeline outputs pass automated data quality checks before being promoted to production.

Requirements

Must Have

• Bachelor's degree or higher in Computer Science, Information Technology, or a related field.
• 5+ years of experience in Data Engineering, ETL Development, or a related field, with proven ownership of production data pipelines.
• Strong hands-on experience with Snowflake, including warehouses, schemas, access control, query performance tuning, and implementation-level design.
• Advanced SQL skills, with the ability to independently handle complex transformations, window functions, large-scale reconciliation queries, and performance optimization.
• Solid understanding of ETL and data pipeline concepts, including transformation logic, data lineage, data quality, monitoring, and observability.
• Proficiency in Python for pipeline automation, data processing, and tooling integration.
• Hands-on experience with dbt, Airflow, or equivalent orchestration and transformation tools, including configuration and maintenance.
• Good understanding of data security, PII handling, access control, and compliance requirements within regulated data environments.
• Experience working with data in healthcare, pharmaceutical, financial services, or other regulated industries.
• Ability to effectively review and guide AI-generated code, identifying correctness, security, performance, and overall quality issues.
• Business-level English proficiency, with the ability to work with English-language data specifications, technical documentation, and delivery requirements.

Nice to Have

• Experience working with marketing automation platforms and their data models, such as Marketo, Salesforce Marketing Cloud, or equivalent platforms.
• Exposure to AI-enabled data engineering tools and architectures, such as Snowflake Cortex, LLM-assisted pipeline development, or feature store architecture.
• Experience working with healthcare or pharmaceutical data under HIPAA or similar compliance requirements.