Data Engineer（Senior Level）

Xiaomi Technology; Kuala Lumpur; On-site; MYR 240,000 - 420,000; Full time

Job summary

Xiaomi Technology is seeking a senior data engineer to lead the design and evolution of its overseas data warehouse and data platform across mobile, IoT, and app data domains. You will architect scalable data processing systems and implement analytics applications to transform raw data into actionable insights.

The role requires expertise in big data tech (Spark, Flink, Hadoop), data modeling, and building data products such as dashboards.

Qualifications

• Bachelor’s degree or above in Computer Science, Data Engineering, or a related field.
• 5+ years of experience in data engineering or data platform development.
• Proficiency in big data technologies (Spark, Flink, Hadoop ecosystem).
• Solid experience in data modeling and large-scale data warehouse design.
• Programming in Python, Java, or Scala.
• Hands-on ML/NLP or advanced analytics workflows preferred.
• Experience with data visualization tools and building data products.

Responsibilities

• Lead the design, development, and evolution of overseas data warehouse and data platform across mobile, IoT, and app data domains.
• Architect scalable data processing systems and analytics applications to transform raw data into insights.
• Apply NLP and ML techniques to extract value from large-scale datasets.
• Design and optimize batch and real-time data pipelines (Spark, Flink) for performance and reliability.
• Define data warehouse architecture and governance (ODS, DWD, DWS, ADS).
• Develop data products including dashboards, visualization systems, and reporting solutions.
• Collaborate with business and analytics teams to translate requirements into scalable data solutions.
• Mentor junior engineers and promote best practices in data engineering.

Skills

Python

Java/Scala

Big data

Education

Bachelor's degree in Computer Science or Data Engineering

Tools

Spark

Flink

Hadoop ecosystem

Job description

Job description：

• Lead the design, development, and evolution of the company’s overseas data warehouse and data platform across mobile device, IoT, and app data domains
• Architect and implement scalable data processing systems and analytics applications to transform raw data into actionable insights
• Apply advanced data mining, data modeling, natural language processing (NLP), and machine learning techniques to extract value from large-scale structured and unstructured datasets
• Design and optimize batch and real-time data pipelines (e.g., Spark, Flink), ensuring high performance, scalability, and reliability
• Define and implement data warehouse architecture (ODS, DWD, DWS, ADS layers) and data governance practices (data quality, lineage, metadata)
• Drive the development of data products, including dashboards, visualization systems, and dynamic reporting solutions
• Partner with business, product, and analytics teams to translate complex requirements into scalable data solutions
• Mentor junior engineers and promote best practices in data engineering and analytics

Requirement：

• Bachelor’s degree or above in Computer Science, Data Engineering, or a related field
• 5+ years of experience in data engineering or data platform development
• Strong expertise in big data technologies (e.g., Spark, Flink, Hadoop ecosystem)
• Solid experience in data modeling and large-scale data warehouse design
• Proficiency in programming languages such as Python, Java, or Scala
• Hands-on experience with machine learning, NLP, or advanced analytics workflows is highly preferred
• Experience with data visualization tools and building data products (e.g., dashboards, reporting systems)
• Strong understanding of both structured and unstructured data processing
• Proven ability to optimize large-scale data systems and pipelines
• Excellent communication and stakeholder management skills
• Experience with global or overseas data environments is a plus. Ability to communicate in Mandarin and English, in order to support coordination and collaboration with Mandarin-speaking stakeholders, teams, and business partners across regional markets.