Head of Product

Engineering Manager (Data Platform)

Ho Chi Minh - Viet Nam

Offshore

• Data Engineering
• Management

Agile Team Leadership: Guide and coach Agile teams to uphold engineering standards, manage sprint backlogs, clarify responsibilities, ensure code quality, enforce development guardrails, and drive rigorous testing practices. Agile Data Delivery: Oversee Agile execution across data platforms, maintaining excellence in data quality, testing, code review practices, CI/CD pipelines, documentation, and operational readiness. Cross-Functional Collaboration: Partner with data architects, product managers, analytics teams, platform engineers, and governance stakeholders to deliver data capabilities aligned with business priorities. Roadmap Ownership: Lead the execution of the data engineering roadmap, balancing immediate delivery needs with long-term platform sustainability. Architecture & Design: Contribute to the design of data platform architecture across ingestion, transformation, storage, and consumption layers. Engineer Development: Coach engineers to become T-shaped professionals, capable of working across batch processing, streaming, analytics engineering, and platform operations. Technical Debt Remediation: Own and prioritize the resolution of technical and data debt, including legacy pipelines, performance bottlenecks, and data quality issues. Modern Practices: Stay current with evolving data engineering tools, methodologies, and patterns-particularly within the Databricks ecosystem. Lifecycle Accountability: Ensure end-to-end ownership of data solutions, from design and build through deployment, monitoring, and ongoing support. Team Empowerment: Foster self-sufficient, disciplined teams accountable for the reliability and resilience of data products. Process Excellence: Lead initiatives to enhance data delivery through automation, observability, and operational best practices. Continuous Improvement: Inspire teams to innovate, experiment, and embrace continuous delivery as part of their culture. Career Growth: Drive career development for data engineers, partnering with HR to manage performance and define growth pathways.

Negotiation

Featured Job

SME Digital Banking Head

Ha Noi - Viet Nam

Product, Bank

• Sale

Lead the development and execution of the SME business strategy in line with overall corporate goals. Identify and capitalize on growth opportunities within the SME sector and create actionable business plans. Continuously monitor market trends, competitor activities, and regulatory changes to adapt strategies effectively. Drive the acquisition of new SME clients and strengthen relationships with existing ones. Develop and oversee the implementation of innovative SME banking products and services, including loans, deposits, trade finance, and digital solutions. Work closely with marketing teams to design campaigns targeting the SME segment. Establish, lead, and mentor a high-performing SME banking team, including relationship managers and product specialists. Set clear performance targets and ensure the team meets or exceeds revenue, profitability, and customer satisfaction goals. Collaborate with the credit risk team to establish prudent risk assessment frameworks for SME lending. Monitor credit quality and minimize non-performing loans (NPLs) to ensure a healthy portfolio. Act as the key point of contact for SME-related partnerships and collaborations with external stakeholders. Represent the organization in SME forums, conferences, and events to enhance brand visibility. Improve customer experience and operational efficiency by streamlining processes and leveraging technology and digital platforms to enhance service delivery for SME clients. Ensure compliance with local and international banking regulations and maintain robust internal controls and reporting mechanisms for all SME banking activities.

Negotiation

Product Manager (Data & Models)

Ho Chi Minh - Viet Nam

Product

• Product Management
• AI

Designing data strategy and model integration for creating efficient data pipelines, evaluation frameworks, and annotation systems to maintain high-performance LLMs. Responsible for ensuring data quality standards and implementing bias mitigation and privacy-preserving techniques. Defining the product's core model roadmaps, taking into account technical feasibility, user needs, and ethical considerations. Collaboration with researchers to incorporate experimental breakthroughs into deployable features. Partnering with Engineering and Research teams to ensure model development aligns with product goals and advocating for transparency in model decision-making to build user trust. Analyzing usage patterns from open-source communities (Discord, Reddit, GitHub) to refine model behavior and address real-world edge cases, contributing to community-driven model evolution. Setting performance benchmarks, cost efficiency, and resource utilization standards for model scalability and reliability.

Negotiation