Job Description

This role will play a critical part in supporting the delivery of Prudential Assurance Company Singapore strategic objectives captured as part of the Analytics Roadmap. You will collaborate closely with Data and Analytics Centre of Excellence (CoE), technology and business teams. The role is responsible for progressing Prudential Singapore’s business growth by building world-class systems, processes and engineering standards that enable advanced analytics and machine learning at scale. You will build data solutions, processes, and standards by developing use cases defined in the roadmap.

• Build pipelines to ingest a wide variety of data from multiple sources within the organization and from external sources (e.g., government, vendors, and social media).
• Optimize existing pipelines .
• Testing data structures to ensure that they are fit for use for data analysts and scientists.
• Prepare and maintain environments for secure prototyping, development, testing and data manipulation for data scientists.
• Design and implement effective data storage solutions and models.
• Assist data models and AI/ML deployment.
• Assess database implementation procedures to ensure they comply with internal and external regulations.
• Prepare accurate database design and architecture reports for management and executive teams.
• Oversee the migration of data from legacy systems to new solutions on Cloud infrastructure.
• Monitor the system performance by performing regular tests, troubleshooting, and integrating new features.
• Automate low value tasks

• Experience with at least one major Cloud Infrastructure provider (Azure/AWS/GCP)
• Experience building data pipelines using batch processing with Apache Spark (Spark SQL, DataSet / Dataframe API) or Hive query language (HQL)
• Knowledge of Big Data ETL processing tools
• Experience in Data Modelling, Data mapping for Data Warehouse and Data Marts solutions
• Experience with Hive and Hadoop file formats (Avro / Parquet / ORC)
• Basic knowledge of scripting (shell / bash)
• Experience of working with multiple data sources including relational databases (SQL Server / Oracle / DB2 / Netezza), NoSQL / document databases, flat files
• Understanding of CICD tools such as Jenkins, JIRA, Bitbucket, Artifactory, Bamboo and Azure Dev-ops.
• DevOps practices using Git version control
• An interest in staying up to date with industry standards and technological advancements that will improve the quality of your outputs.
• Ability to debug, fine tune and optimize large scale data processing jobs
• Highly capable inPython or Scala
  SQL
  DataBricks
  
• Knowledge inAzure Data Factory
  Azure DevOps
  BitBucket or GitHub
  Machine learning
  MLFlow
  ML (Machine Learning) frameworks (e.g., scikit-learn, TFX, PyTorch etc.).
  
• Knowledge of life insurance industry preferred.

• Flexibility, creativity, and the capacity to receive and utilize constructive feedback.
• Curiosity and outstanding interpersonal skills.
• Work as a team player
• Capacity to successfully manage a pipeline of duties with minimal supervision.

• Master’s degree or equivalent work experience in Computer Science or related discipline.
  
  
• Certificates in Data Engineering from reputable MOOCs or cloud vendors are welcome