Skill diminta
AWSAzureCommunicationDeliveryGCPJapaneseLeadershipMentoring
Gaji pasar untuk posisi ini
Median Rp8,9 jt/bulan · rentang umum Rp7,4 jt – Rp11 jt
Berdasarkan 224 lowongan DevOps & Infrastructure se-Indonesia (semua level).
Lihat data gaji selengkapnya →Deskripsi
- Job description for Databricks Team Leader at Công ty TNHH Diksha Technologies
- Key Responsibilities
- Engineering Team Leadership
- Lead and supervise a remote engineering team of 5–10 data engineers and AI developers.
- Provide technical guidance, mentoring, and support to team members.
- Coordinate task assignments, monitor progress, and maintain engineering quality standards.
- Data Platform Architecture & Development
- Design and oversee scalable data pipelines and data processing solutions using Databricks.
- Provide architectural direction for data engineering and AI infrastructure.
- Guide the team in implementing cloud-based data solutions.
- Japanese Stakeholder Collaboration
- Act as the primary technical communication point between Japanese stakeholders and the Vietnam engineering team.
- Analyze business requirements and translate them into technical specifications and solution architectures.
- Maintain clear communication and alignment throughout project delivery.
- Project Execution & Quality Management
- Manage delivery schedules, project milestones, and engineering assignments.
- Oversee code quality and technical implementation.
- Facilitate Agile/Scrum activities to support effective team collaboration.
- AI & LLM Technology Integration
- Guide the engineering team in adopting modern generative AI and large language model technologies.
- Support the use of LLM application development platforms such as Dify.
- Provide technical direction involving NVIDIA NeMo and related AI frameworks based on project requirements.
- Required Qualifications
- Technical Expertise
- Proven experience in data engineering, big data technologies, and cloud-based data pipeline development.
- Strong practical knowledge of Databricks and its application in data engineering solutions.
- Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.