Data Engineer - China Innovation Hub


  • Excellent communication skills in English and Mandarin (both oral and written)
  • Bachelor's degree in Computer Science with Mathematics and Statistics or equivalent subject; Master's degree preferred
  • 2-4 years of experience in big data related software development, experienced with data modeling, design patterns, and building highly scalable and secured solutions
  • Familiar with big data platforms like SQL, Teradata, Hadoop, Spark
  • For data integration engineers, experienced in programming languages such as Java, C/C++, Python and R; For user experience data engineers, experienced in UI design and Javascript application development. Mobile app development experience is a plus.
  • Knowledge of agile software development process
  • Passion for machine learning and innovation
  • Strong analytical and problem-solving skills paired with the ability to develop creative and efficient solutions, with tolerance to deal with bad quality data
  • Ability to work effectively in teams with good conceptual to technical communication skills

Who You'll Work With

Joining China Innovation Hub at our Shanghai Office, you will be part of an avant-garde internal start-up delivering world-class data applications to generate lasting impact for McKinsey's notable clients in Greater China and beyond.

China Innovation Hub (CIH) is a rapidly growing practice within McKinsey's Greater China office. It provides distinctive end-to-end services to our clients on a wide variety of innovation related topics, including digital implementation, new digital business setup, big data analytics, digital / physical product design, digital marketing, and digital center for operations excellence etc.

You'll be actively cooperating with data scientists and digital consultants to incorporate clients' requirements and impactful analysis into our data products. You'll also be an expert in data engineering and advising relevant people at the firm on technical aspects of analytics engagements.

What You'll Do

Data engineers sit at the core of a big data revolution, which brings McKinsey's rich business acumen and advanced analytics experience into production on a massive scale, both at our clients' site and internally at the firm as a platform.

For data integration engineers, you'll own the process of defining, designing and implementing the end-to-end data pipelines including data ingestion, rationalization, transformation, storage and query, in the context of both conventional and big data technologies. You'll need to apply machine learning algorithms and incorporate advanced analytics models to maximize business value and impact from the data. You'll also work with front-end engineers to lay down the back-end foundation of our data applications, minding non-functional requirements such as security, reliability and system performance.

For user experience data engineers, you'll be the creator of an unparalleled mobile and web user interface which is engaging, performant and, above all, value-adding to users of our applications. You'll need to sympathize with users and bring deep experience in UX/UI design and popular front-end technologies. You should be comfortable creating "imperfect" code for the purpose of testing and have a clear understanding of how something will be used in the real world.

To deliver a self-serve analytical solution to clients, you'll embrace an agile software development environment, develop software which ensures proper data quality controls at all levels and engages clients with clear meaningful outcomes.

Working with McKinsey as part of the China Innovation Hub provides you with rewarding and challenging opportunities, including: a) Shaping the problems as well as the solutions as a thought partner to the business; helping clients to translate big ideas into reality with delivered insights; b) Innovating new tools and techniques in an encouraging environment and applying your understanding of insights in real business settings; and c) Being exposed to an enormous variety of topics across many different industries such as a world-leading bank figuring out how best to carry out customer service across all of its channels, a fast growing internet company trying to retain the best talents, or an Auto OEM reducing lead generation costs.

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