Data Engineer Manager

Hangry; Jakarta Pusat; On-site; IDR 250,000,000 - 420,000,000; Full time

Job summary

Hangry is seeking a data engineer to design and optimize scalable, cost-efficient end-to-end data architectures. You will improve data delivery speed and engineering efficiency year over year, building reusable frameworks and automation while maintaining reliable pipelines and real-time systems.

You will deliver production-ready solutions on tight timelines, resolve complex production issues, and evaluate new tools with cost-benefit analysis.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• Minimum 3 years of experience in data engineering or related roles.
• Strong experience building and operating production-scale data systems.
• Hands-on experience with data pipelines, data warehouses/lakes, and cloud platforms.
• Solid understanding of batch and streaming data processing.
• Experience supporting analytics, machine learning, or AI data workflows.
• Strong problem-solving skills in complex production environments.
• Strong judgment in balancing speed, quality, cost, and scalability.
• Clear communication skills with both technical and non-technical stakeholders.

Responsibilities

• Design and optimize scalable, cost-efficient end-to-end data architectures.
• Improve data delivery speed and engineering efficiency year over year.
• Build reusable frameworks, templates, and automation to reduce repetitive work.
• Develop and maintain reliable data pipelines, real-time systems, and analytics platforms.
• Deliver production-ready solutions under tight timelines without compromising quality.
• Resolve complex production issues independently and implement long-term fixes.
• Evaluate new tools, frameworks, and architectures with clear cost–benefit analysis.
• Proactively reduce technical debt and prevent recurring scalability issues.
• Make and communicate technical trade-offs (e.g., batch vs. streaming, build vs. buy).
• Apply advanced data or analytics concepts in production systems.
• Act as a technical authority through code reviews, design reviews, and best practices.
• Collaborate with stakeholders and translate technical decisions into business impact.

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field

Minimum 3 years of experience in data engineering or related roles

Strong experience building and operating production-scale data systems

Hands-on experience with data pipelines, data warehouses/lakes, and cloud platforms

Solid understanding of batch and streaming data processing

Experience supporting analytics, machine learning, or AI data workflows

Strong problem-solving skills in complex production environments

Strong judgment in balancing speed, quality, cost, and scalability

Clear communication skills with both technical and non-technical stakeholders

Job description

• Design and optimize scalable, cost-efficient end-to-end data architectures.
• Improve data delivery speed and engineering efficiency year over year.
• Build reusable frameworks, templates, and automation to reduce repetitive work.
• Develop and maintain reliable data pipelines, real-time systems, and analytics platforms.
• Deliver production-ready solutions under tight timelines without compromising quality.
• Resolve complex production issues independently and implement long-term fixes.
• Evaluate new tools, frameworks, and architectures with clear cost–benefit analysis.
• Proactively reduce technical debt and prevent recurring scalability issues.
• Make and communicate technical trade-offs (e.g., batch vs. streaming, build vs. buy).
• Apply advanced data or analytics concepts in production systems.
• Act as a technical authority through code reviews, design reviews, and best practices.
• Collaborate with stakeholders and translate technical decisions into business impact.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum 3 years of experience in data engineering or related roles.
• Strong experience building and operating production-scale data systems.
• Hands-on experience with data pipelines, data warehouses/lakes, and cloud platforms.
• Solid understanding of batch and streaming data processing.
• Experience supporting analytics, machine learning, or AI data workflows.
• Strong problem-solving skills in complex production environments.
• Strong judgment in balancing speed, quality, cost, and scalability.
• Clear communication skills with both technical and non-technical stakeholders.