Working location: Kai Tak
Employment period: 1-year contract (For internal application, only short-term employment contract’s terms and condition will be offered for this position regardless of job applicant’s current job category)
Main Responsibilities
- Build end-to-end data pipelines including data collection, transformation, quality and integration solutions to facilitate CLP’s data & analytics solutions.
- Collaborate with solution design and business requirements teams to identify data requirements and assemble large, complex data sets that meet the requirements
- Design, implement and fine-tune analytics solutions that meet business and technical requirements
- Work collaboratively with the CLP data architect to ensure data model integrity
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
- Create data tools for analytics and data scientists teams that assist them in building and optimising the data models and solutions
- Work with the DevOps engineer to support the consistent operation of data & analytics solutions
- Work closely with the data analysts & data scientists to design and develop APIs
Requirements
Academic Qualification:
- Bachelor or Masters degree in a related field (e.g. computer science, information technology, etc.)
Professional Experience:
- At least 5 years experience in SQL/PostgreSQL, data and BI solutions with integration to 3rd party tools
- Experience working with application server software (e.g. ERP), Spark, Scala, Python, SQL scripting languages, relational databases (e.g. SQL DB/DW), NoSQL platforms (e.g. HBase, MongoDB, Cassandra), cloud technologies (e.g. Azure)
- Hands-on experience designing, building, and delivering data solutions on Databricks (mandatory)
- Demonstrated experience delivering data engineering projects using Databricks (Spark, notebooks, pipelines) (mandatory)
- Experience with Data Lake, Data Factory, BI Dashboard, and BI implementation projects
- Highly experienced with processing large and complex datasets and building end-to-end data pipelines using on-premise or cloud-based data platforms
- Experienced in coding in data management, data warehousing or unstructured data environments
- Experience in the energy sector or other asset-intensive industries will be highly regarded
- Experience in using coding assistants (e.g. GitHub Copilot) for uplifting productivity in development
- Familiar with GenAI concepts like RAG, orchestration frameworks like LangChain and LlamaIndex, vector databases etc. to collaborate efficiently with data scientists and ML engineers in AI use cases
Competencies Technical (Functional):
- Experience in Azure cloud platforms and technology
- Ability to define and develop data integration patterns and pipelines
- Strong knowledge of data modelling, data warehousing, and BI concepts
- Self-motivated, able to work independently, and attention to details
- Curious about emerging AI trends and their implications for data engineering
What We Do
The CLP Group is one of the largest investor-owned power businesses in Asia Pacific with investments across Hong Kong, Mainland China, Australia, India, Taiwan Region and Thailand. Hong Kong-listed CLP Holdings Limited is the holding company for the CLP Group, which has a diversified portfolio of generating assets that uses a wide range of fuels including coal, gas, nuclear and renewable sources. Through CLP Power Hong Kong Limited, the Group operates a vertically integrated electricity supply business that provides a highly reliable supply of electricity to 80% of Hong Kong’s population. The CLP Group is the largest external investor in the energy sector in Mainland China. The Group’s wholly-owned subsidiary EnergyAustralia is a leading integrated energy company in Australia, providing gas and electricity to about 2.46 million households and businesses. Apraava Energy, in which CLP has a 50% interest, is one of India’s biggest renewable energy producers with operations in power generation and transmission. CLP Holdings is included in the Global Dow – an index of the world’s leading blue-chip companies, in addition to sustainability-focused indices including the Dow Jones Sustainability Asia Pacific Index (DJSI Asia Pacific), the Hang Seng Corporate Sustainability Index Series and the FTSE4Good Index series.
