Lead Data Engineer (AWS SageMaker Expertise)

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. Job Description: We are looking for a talented Lead Data Engineer with specialized expertise in AWS SageMaker to join our team in Jakarta, Indonesia. The ideal candidate will have a strong background in data engineering, cloud computing, and machine learning, with a focus on leveraging AWS SageMaker for scalable and efficient model development and deployment. Fluency in both Bahasa and English languages is required for effective communication with our diverse team and clients. 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. Powered by JazzHR