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- Develop and maintain robust, scalable, and efficient data architectures to support AI/ML product development.
- Define and enforce best practices for data pipelines, storage, and retrieval to enable seamless AI/ML workflows.
- Design, build, and maintain highly scalable and fault-tolerant ETL/ELT pipelines to process large volumes of structured and unstructured data.
- Ensure data availability, quality, and reliability to support analytics and AI/ML model performance.
- Architect, implement, and optimize cloud-based data solutions using AWS services such as S3, Glue, Redshift, Lambda, EMR, Athena, Kinesis, and DynamoDB.
- Utilize infrastructure-as-code (IaC) tools like AWS CloudFormation or Terraform to automate deployments and manage cloud resources efficiently.
- Partner with stakeholders to define data requirements and align them with business objectives.
- Implement and manage data governance policies to ensure compliance with relevant regulations and internal standards.
- Leverage AWS security features (e.g., IAM, KMS, VPC) to safeguard sensitive data.
- Minimum of 3 years of hands-on experience in data engineering, with a proven track record in designing and implementing data pipelines and cloud-based solutions.
- Advanced expertise in the AWS ecosystem, including services such as S3, Glue, Redshift, Athena, EMR, Lambda, and DynamoDB.
- Proficiency in programming languages like Python, Scala, or Java.
- Solid experience with SQL and NoSQL databases.
- Strong knowledge of CI/CD pipelines and version control systems (e.g., Git).
- Excellent problem-solving and analytical skills.
- Effective communication skills, with the ability to translate technical concepts for non-technical stakeholders.
- AWS certifications such as AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect.
- Experience collaborating with AI/ML teams and deploying AI-driven applications.
- Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes).
- Knowledge of big data tools such as Hive, Presto, or Hadoop.
- Unlock Your Growth Potential: Benefit from unparalleled support for your professional development with Certis Corporate University, the first of its kind in Asia.
- Empower Change: Make a lasting impact through innovative initiatives that transform local communities and global industries.
- Join a Culture of Innovation: Be a part of our team of innovators, working together to drive technological advancements towards a Safer, Smarter, And Better tomorrow for all.
- Develop and maintain robust, scalable, and efficient data architectures to support AI/ML product development.
- Define and enforce best practices for data pipelines, storage, and retrieval to enable seamless AI/ML workflows.
- Design, build, and maintain highly scalable and fault-tolerant ETL/ELT pipelines to process large volumes of structured and unstructured data.
- Ensure data availability, quality, and reliability to support analytics and AI/ML model performance.
- Architect, implement, and optimize cloud-based data solutions using AWS services such as S3, Glue, Redshift, Lambda, EMR, Athena, Kinesis, and DynamoDB.
- Utilize infrastructure-as-code (IaC) tools like AWS CloudFormation or Terraform to automate deployments and manage cloud resources efficiently.
- Partner with stakeholders to define data requirements and align them with business objectives.
- Implement and manage data governance policies to ensure compliance with relevant regulations and internal standards.
- Leverage AWS security features (e.g., IAM, KMS, VPC) to safeguard sensitive data.
- Minimum of 3 years of hands-on experience in data engineering, with a proven track record in designing and implementing data pipelines and cloud-based solutions.
- Advanced expertise in the AWS ecosystem, including services such as S3, Glue, Redshift, Athena, EMR, Lambda, and DynamoDB.
- Proficiency in programming languages like Python, Scala, or Java.
- Solid experience with SQL and NoSQL databases.
- Strong knowledge of CI/CD pipelines and version control systems (e.g., Git).
- Excellent problem-solving and analytical skills.
- Effective communication skills, with the ability to translate technical concepts for non-technical stakeholders.
- AWS certifications such as AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect.
- Experience collaborating with AI/ML teams and deploying AI-driven applications.
- Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes).
- Knowledge of big data tools such as Hive, Presto, or Hadoop.
- Unlock Your Growth Potential: Benefit from unparalleled support for your professional development with Certis Corporate University, the first of its kind in Asia.
- Empower Change: Make a lasting impact through innovative initiatives that transform local communities and global industries.
- Join a Culture of Innovation: Be a part of our team of innovators, working together to drive technological advancements towards a Safer, Smarter, And Better tomorrow for all.