About this role

At least 5 years continuous experience in data engineering area.

E. B.Sc. or M.Sc. in Computer Science, Engineering, Information Technology or equivalent work experience.

Strong knowledge and hands on experience of big data technologies such as data lakes, Apache Spark, Flink, Kafka etc.

Good knowledge of data warehousing concepts and ETL processes, DevOps, CI/CD and software testing.

Expertise with one of programming languages such as SQL, or Python.

Have working experience of AWS (Redshift, EMR, S3) and Azure (Data Factory, Power BI service) data analytics services.

Experience with Data platform tools like Databricks and/or Snowflake.

Be able to use Power BI for data analytics and visualization.

Be able to manage data platform with IaC (Infrastructure as Code) will be preferred.

Experience with connectivity data in automotive industry will be preferred.

Fluent in English with Chinese skill as a plus

Responsibilities and Deliveries

Design, develop and maintain scalable batch and stream data pipelines to ingest data into platform from various sources, use tools to automate and orchestrate data pipelines

Develop and implement data processing workflows of cleansing, deduplication, and transformation processes to prepare data for data services

Operate and maintain platform with infrastructure team.

Perform data platform upgrade test including regression test, security test, functional test.

Implement checks and measures to ensure the security, accuracy, completeness, and consistency of data

Set up tools to monitor pipeline performance, data quality, and system health

Diagnose and resolve issues with data pipelines, storage systems, or integrations

Collaborate with stakeholders to define data models and ensure the data meets their needs

Provide technical guidance and data access support to data consumers and addressing technical challenges.

Document data pipelines, architectures, and workflows to ensure clarity and ease of mainten

Responsibilities