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Data Engineer (AI), contract

Morgan McKinley Hong Kong
Full time Contract On-site Competitive

About the job

Responsibilities
  • Develop and manage end-to-end data pipelines, covering data ingestion, transformation, quality assurance, and integration to support enterprise analytics solutions.
  • Partner with solution design and business stakeholders to define data needs and compile complex datasets aligned with business objectives.
  • Design, implement, and optimize analytics solutions to meet both technical and functional requirements.
  • Collaborate with data architects to maintain consistency and integrity of data models.
  • Build and maintain scalable infrastructure for efficient data extraction, transformation, and loading (ETL) across diverse data sources.
  • Develop tools and frameworks to enable data analysts and data scientists to efficiently build and enhance data models.
  • Work closely with DevOps teams to ensure stable and reliable deployment and operation of data platforms.
  • Collaborate with data analysts and scientists to design and develop APIs supporting analytics and AI use cases.
Requirements
  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related discipline.
  • Minimum 3 years of experience in SQL/PostgreSQL, data engineering, and BI solutions, including integration with third-party systems.
  • Hands-on experience with technologies such as ERP systems, Spark, Scala, Python, SQL scripting, relational databases (e.g., data warehouses), NoSQL platforms (e.g., MongoDB, Cassandra), and cloud platforms (e.g., Azure).
  • Proven experience with modern data platforms and tools such as Data Lake, Databricks, Data Factory, and BI dashboard development.
  • Strong track record in handling large-scale, complex datasets and building end-to-end pipelines on both on-premise and cloud environments.
  • Proficiency in coding for data management, data warehousing, and unstructured data processing.
  • Experience in energy or other asset-heavy industries is advantageous.
  • Familiarity with developer productivity tools such as GitHub Copilot.
  • Understanding of Generative AI concepts (e.g., RAG), orchestration frameworks (e.g., LangChain, LlamaIndex), and vector databases.