AI Data Engineering Leader

3 days ago


Singapore Certis Full time

We're seeking a seasoned Data Engineer to spearhead transformative initiatives at Certis, shaping the future of AI.

In this pivotal role, you'll design, build, and manage cutting-edge infrastructure and data pipelines, enabling advanced AI solutions that drive innovation. Your expertise in AWS technologies is critical, as our development environment is deeply rooted in AWS cloud services.

You'll collaborate closely with data scientists, machine learning engineers, and software developers to deploy AI models and applications effectively. Partnering with stakeholders, you'll define data requirements and align them with business objectives.

Responsibilities
  • Data Strategy & Architecture: Develop and maintain robust, scalable, and efficient data architectures to support AI/ML product development.
  • Data Pipelines: Design, build, and maintain highly scalable and fault-tolerant ETL/ELT pipelines to process large volumes of structured and unstructured data.
  • Data Security & Compliance: Implement and manage data governance policies to ensure compliance with relevant regulations and internal standards.

You'll leverage AWS security features (e.g., IAM, KMS, VPC) to safeguard sensitive data and utilize infrastructure-as-code (IaC) tools like AWS CloudFormation or Terraform to automate deployments and manage cloud resources efficiently.

Requirements: 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, and strong knowledge of CI/CD pipelines and version control systems (e.g., Git). Excellent problem-solving and analytical skills, effective communication skills, and ability to translate technical concepts for non-technical stakeholders.


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