What you'll do
The Manufacturing &Supply Chain hub team looks after the data and analytics needs of business areas across M&SC, largely through engagement with teams embedded within business functions. The D&A Delivery team’s responsibility within the hub will be to deliver data and analytical products following a prioritised backlog of use-cases, and hand over to our business units to manage them.

Design and construct high-performance robust data pipelines.
Develop and maintain scalable data processing systems.
Ensure data quality and integrity in pipelines and databases.
Optimize data retrieval and develop dashboards for data visualization.
Implement data security and privacy policies.
Collaborate with business stakeholders, transformation leads, data governance leads, and architects to gather requirements and deliver analytical solutions.
Be a positive source of positivity within D&A, vocally supporting and encouraging the strategy and transformation.
Proactively communicate the D&A vision and mission through informal channels.
Embody the Volvo values and D&A cultural principles.
Stay current with industry trends and technologies.




What you'll bring
Bachelor's or Master's degree in information management, data science, computer science, or equivalent by experience. 2-5 years of hands-on experience in Data Engineering.
Proficiency in SQL and experience with relational databases, query authoring, as well as working familiarity with a variety of databases.
Ability to articulate data concepts to stakeholders at all levels and foster a culture of data-driven decision-making across the organization.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Knowledge of data ingestion methods (CDC, API, streaming) and formats (JSON, Parquet, Iceberg)
Experience with version control like Git.
Strong analytical skills and problem-solving aptitude.
Excellent communication skills in English and Mandarin.
Strong teamwork skills, ownership mentality, and a can-do attitude.
Experience with dbt or data processing pipelines and data warehousing is beneficial.
Working in agile teams with scrum / SAFe. Knowledge of the data mesh concepts.
Experience with knowledge graphs and semantic modelling.
Experience with big data tools (Hadoop, Spark, Kafka, etc.) and data pipeline and workflow management tools.