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Data Engineer/ Senior Engineer

Date:  21-May-2023
Location: 

StarHub Green

Company:  StarHub Ltd

Job Description

Purpose

  • Work with data to solve business problems, building and maintaining the infrastructure to answer questions and improve processes
  • Define optimal solutions to data collection, processing and warehousing for data scientists and business analysts to interpret and make data accessible to meet business requirements
  • Subject matter expert in data engineering and data pipeline with adoption of best practices and innovations
  • Work closely with different stakeholders to support the project implementation and maintenance of existing or new data platforms on cloud


Responsibilities

  • Design, implement and maintain data collection, data flow channels, data processing systems and warehousing that support the collection, storage, batch and real-time processing, and analysis of information in a scalable, repeatable and secure manner in cloud environment
  • Identify, design, and implement internal process improvements including data collection for cross functional teams, automating manual processes, optimizing data flow/delivery, re-designing infrastructure for greater scalability, etc. using SQL and ‘big data’ technologies
  • Collect, parse, manage, analyse and visualise large, complex sets of data to turn information into insights accessible through multiple platforms
  • Ensure data quality and efficiency, including the backup of data and its easy retrieval in case of system failure
  • Build analytic tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics for the use of analytics and data scientist team members
  • Work with stakeholders including Product, Data, Systems, Service Operations teams to resolve data-related technical issues and support their data infrastructure needs
  • Explore ways to enhance data quality and reliability
  • Collaborate with Data Scientists and Architects on analytical projects in developing prescriptive and predictive models
  • Prepare and maintain proper documentations of data pipeline design and processes, operation procedures, etc
  • Be an advocate for best practices and continuous learning, keeping track of industry standards and technological advances that can improve the framework structure and design
     

Qualifications

  • Appropriate qualification in Computer Science, IT, or Applied Mathematics, including Data Engineering certifications such as IBM Certified Data Engineer, Google Certified Professional or equivalent
  • At least 3 years of experiences as data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up
  • Passionate about working with large data sets, data model and interpret data pattern
  • Ability to understand business processes and resolve challenges with data models, data mining, and segmentation techniques
  • Knowledge of data migration and integration techniques, along with the tools necessary to accomplish them
  • Hands-on experiences in transforming functional specifications into design specifications
  • Possesses hands-on experiences in building or maintaining ETL processes and SQL database design
  • Knowledge of programming languages (e.g. Java and Python)
  • Experiences to develop reports and visuals through any Business Intelligent tools
  • Familiar with AWS/GCP data pipeline and ecosystem, data warehouse and big data platforms such as Hadoop solutions
  • Good problem solving and communication skills, especially for explaining technical concepts to non-technical business leaders
  • Ability to work in a dynamic, research-oriented team that has concurrent projects
  • Certification in Cloud Technology platform (in Architecture or Networking), Container Architecture, Systems and/or Network Virtualization
  • Knowledge of telco network such as Mobile and Fixed will be advantageous
  • Passion for software development, automation and new technologies/innovations for business and in operational excellence
     

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