Data Engineer Manager
Job Title : Data Engineer Manager Mitr Phol AI (MAI)
Location : Ploen chit, Bangkok
Role Overview
The Data Engineering Manager leads MAI's data delivery team to ensure high-impact data work is prioritized, delivered predictably, and executed to enterprise standards. This role owns sprint execution and stakeholder prioritization (60%) while providing technical direction, quality guardrails, and coaching to the Data Engineering and Data Analytics team (40%). The objective is to deliver trusted, secure, and reusable data products that enable MAI use cases across business units.
Key Responsibilities
A) Delivery & Stakeholder Management (60%)
Own the data delivery backlog end-to-end: intake, clarification, sizing, prioritization, and readiness.
Facilitate prioritization with MAI squads, PMO, and BU stakeholders based on value, urgency, dependencies, and capacity.
Lead sprint ceremonies (planning, daily, review/demo, retrospective) and ensure delivery discipline and predictable throughput.
Manage scope changes and competing requests; drive clear trade-offs and decisions to minimize churn.
Remove delivery blockers across IT/Infra/Security/ERP/vendors; escalate risks early and drive closure.
Provide transparent delivery reporting (weekly/monthly): progress, risks, dependencies, and decisions required.
B) Technical Leadership & Team Coaching (40%)
Provide technical direction for data ingestion, transformation, modeling, and serving patterns; ensure solutions are scalable and maintainable.
Define and enforce quality gates (accuracy, completeness, timeliness, consistency) with automated checks where applicable.
Establish operational expectations: monitoring, alerting, incident response, and root-cause analysis for data issues.
Guide engineering best practices: code review, version control, testing, documentation, and release discipline.
Ensure security and compliance-by-design (access control, auditability, PDPA alignment) in collaboration with governance and security functions.
Coach and develop Data Engineers and Data Analysts; build capability, set clear expectations, and promote continuous improvement.
Key Deliverables
A prioritized data backlog aligned to MAI strategic projects, with clear sprint goals and delivery plans.
Production-ready data pipelines and curated datasets with data dictionary, ownership, and documentation.
Data quality framework and SLA definition for critical datasets, including monitoring and alerting.
Standard templates and playbooks (intake form, story format, Definition of Ready/Done, release checklist, incident process).
Qualifications
Required
Bachelor's degree in Computer Science, Information Technology, Engineering, or related field (or equivalent experience).
6-10+ years of experience in data engineering / analytics delivery in an enterprise environment.
2+ years of team leadership (people manager or delivery/tech lead responsibility).
Strong stakeholder management skills with the ability to drive prioritization and decisions under ambiguity.
Strong foundation in SQL and data modeling; practical understanding of ETL/ELT concepts, orchestration basics, and data quality practices.
Experience with version control and delivery discipline (e.g., Git, CI/CD concepts, release management).
Clear communication skills across technical and non-technical audiences.
Preferred
Experience integrating multiple source systems (e.g., ERP and operational systems) and handling mixed digital/manual data inputs.
Familiarity with modern data stack concepts (lakehouse/warehouse patterns) and API/event-driven ingestion.
Experience working in governance-controlled environments (role-based access, audit trails, PDPA).
Exposure to enabling AI/ML use cases through feature-ready datasets and reliable pipelines.