**Job Title**:Lead Data Engineer (AWS SageMaker Expertise)
**Location**:Jakarta, Indonesia (Full-Time)
**Company Overview**: Join our team at NorthBay, a US-based software company and AWS Premier Consulting Partner specializing in AWS Cloud, AI/ML, Big Data, and IoT solutions. We are dedicated to delivering innovative and scalable technology solutions to our clients worldwide.
**Qualifications**:
- Bachelor's or master's degree in Computer Science, Engineering, Mathematics, or a related field.
- 7+ years of experience in data engineering, with a proven track record of designing and implementing scalable data solutions.
- Expertise in AWS services, particularly AWS SageMaker, S3, Glue, Lambda, and EC2, with a deep understanding of cloud computing concepts and best practices.
- Proficiency in Python and SQL, with experience in building and optimizing data pipelines using frameworks such as Apache Spark or AWS Glue.
- Hands-on experience with machine learning algorithms, model training, and deployment, preferably using AWS SageMaker.
- Strong problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
- Excellent communication skills in both Bahasa and English, with the ability to explain complex technical concepts to non-technical stakeholders.
**Preferred Qualifications**:
- AWS certifications related to machine learning or big data.
- Experience working with other cloud platforms such as Azure or Google Cloud Platform.
- Familiarity with DevOps practices and tools for automating infrastructure provisioning, configuration management, and continuous integration/continuous deployment (CI/CD).
- Knowledge of containerization technologies such as Docker and orchestration tools like Kubernetes.
**Responsibilities**:
- Lead the design, development, and maintenance of scalable data pipelines and architectures for processing, storing, and analyzing large volumes of data.
- Collaborate with data scientists, software engineers, and business stakeholders to understand requirements and implement solutions that meet business objectives.
- Architect, implement, and optimize machine learning workflows using AWS SageMaker, including data preprocessing, model training, tuning, and deployment.
- Develop and maintain automated processes for model monitoring, evaluation, and retraining to ensure model accuracy and performance over time.
- Stay updated on emerging technologies and best practices in data engineering and machine learning on AWS, and proactively recommend improvements to our infrastructure and processes.
- Mentor junior team members and promote knowledge sharing within the team to foster a culture of continuous learning and growth.
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