Lead Data Engineer / Data Architect

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
Lead the data architecture and discovery phase, including platform architecture, technology evaluation, and assessment of clients' existing data environments.
Establish the technical specification and architecture baseline, ensuring architecture decisions and delivery requirements are aligned across the engagement.
Design and standardize data modeling approaches such as Kimball, Data Vault, or hybrid models based on business and technical requirements.
Document key architecture decisions through Architecture Decision Records (ADRs), including alternatives considered, trade-offs, and rationale.
Define data platform standards for security, governance, compliance, access control, data lineage, PII protection, and auditability.
Provide technical leadership and architectural guidance to Senior Data Engineers, supporting complex technical decisions across projects.
Proactively assess and mitigate data architecture risks, including scalability, integration, security, compliance, performance, and observability.
Establish and maintain data engineering standards and hiring criteria, contributing to the growth and capability development of the data engineering practice.
Requirements
Must-have
Bachelor's degree or higher in Computer Science, Information Technology, Data Engineering, or a related field.
7+ years of experience in Data Engineering, Data Architecture, or a related field, including 3+ years in a Senior/Lead role with responsibility for technical or platform-level decisions.
Strong hands-on data engineering experience, with the ability to contribute at Senior Data Engineer level when required.
Proven experience in designing data platforms or architectures, including assessing existing data systems and defining actionable technical solutions.
Strong understanding of data modeling and data architecture principles, with practical experience applying approaches such as Kimball, Data Vault, or hybrid models.
Solid experience with cloud data platforms and modern data architectures, including data lake, data warehouse, or lakehouse environments.
Strong knowledge of data governance, security, and compliance, including data lineage, access control, PII handling, and auditability.
Experience with data orchestration and pipeline technologies, such as Airflow, dbt, or equivalent.
Experience with Infrastructure as Code, such as Terraform, Pulumi, or equivalent, with the ability to design and review infrastructure solutions.
Ability to review and guide AI-generated code, identifying issues related to correctness, security, performance, and quality.
Strong business-level English, with confidence in communicating technical architecture and recommendations to senior clients, CTOs, architects, and technical stakeholders.
Nice to have
Experience with Data Lakehouse technologies, such as Delta Lake, Apache Iceberg, or Apache Hudi, including understanding of architectural trade-offs.
Strong experience with AWS data services, such as S3, Glue, Athena, Redshift, and Lake Formation, and/or Snowflake.
Experience designing multi-cloud or hybrid-cloud data architectures across AWS, Snowflake, Azure, or GCP.
Knowledge of ML/AI data infrastructure, including feature stores, model registries, data versioning, and data architectures supporting ML workloads.
Experience owning both data architecture and delivery execution within the same client engagement.
Experience establishing architecture standards, mentoring senior engineers, and driving technical best practices across multiple projects.
Experience working in regulated industries, particularly Healthcare, Pharmaceutical, Financial Services, or other compliance-driven environments.
Familiarity with relevant compliance frameworks such as HIPAA, HL7, FHIR, or 21 CFR Part 11.