BOSCH ★ 3.5

Bosch first started in Vietnam with a representative office in 1994. Bosch has its main office in Ho Chi Minh City, with branch offices in Hanoi and Da Nang, and a Powertrain Solutions plant in the Dong Nai province to manufacture push belt for continuously variable transmissions (CVT) in automobiles. In addition, Bosch operates a software and engineering solutions from product engineering, tool development & automation as well as testing & validation solutions (Bosch Global Software Technologies Vietnam).

In July 2014, Bosch set up a new Automotive R&D Center, located in Ho Chi Minh City. The continuous growth of this Centre is in line with Bosch’s strategy in Vietnam, which aims at becoming a manufacturing and R&D hub in the Southeast Asian region. Currently four products are available: connectors, push belt, fuel supply, and diagnosis module (tank leakage).

For further information, please visit our website: www.bosch.com.vn

Job Summary:
As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and data architecture. You will perform various data engineering activities, develop data visualization solutions, and collaborate with cross-functional teams to deliver engineering solutions that harness the power of data.

Key Responsibilities:

1. Data Engineering Activities:
   1. Design, develop, and maintain robust ETL (Extract, Transform, Load) processes to ensure data integrity and availability.
   2. Build and optimize data pipelines for real-time and batch processing using tools such as Apache Spark, Apache Kafka, or similar technologies.
   3. Implement data models and schemas to support analytics and reporting needs.
   4. Monitor and troubleshoot data pipeline performance, ensuring timely data delivery and quality.
   5. Collaborate with data scientists and analysts to understand data requirements and provide necessary data solutions.
2. Develop Data Visualization Solutions:
   1. Create interactive and insightful data visualizations using tools such as Tableau or Power BI to facilitate data-driven decision-making.
   2. Work with stakeholders to gather requirements and translate them into effective visual representations of data.
   3. Ensure that visualizations are user-friendly, accurate, and aligned with business objectives.
3. Collaborate in an Engineering Team:
   1. Work closely with software engineers, data analysts, and other stakeholders to design and implement engineering solutions that leverage data engineering competencies.
   2. Participate in code reviews, design discussions, and agile ceremonies to foster a collaborative engineering culture.
   3. Contribute to the development of best practices, standards, and documentation for data engineering processes.
      
      

• Bachelor’s degree in engineering, Data Engineering, Computer Science, or a related field.
• Proven experience as a Data Engineer at least 5 years.
• Strong understanding of data engineering principles and practices:
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Data Management e.g., SQL, NoSQL, metadata, schema, API, etc.
  • Knowledge of Cloud architectures (Azure).
  • Familiarity with data visualization tools (e.g., Tableau, Power BI) and experience in creating dashboards and reports.
  • Experience in usage of Cloud-programming languages such as Yaml, Python (relevant libraries: numpy, pandas, pyspark).
  • Data processing methodologies and tools/orchestration such as Data factory, Fabric and/ or Databricks workflows.
  • Knowledge of streaming data/IoT solutions (stream analytics or Kafka.)
  • Knowledge/experience in Git.
  • Manage and maintain the tools and infrastructure necessary for CI/CD, including build-servers, code repositories, and deployment automation tools.
  • Knowledge on testing (unit, integration, acceptance, functional).
  • Data governance implementation to build foundation and enable data analytics/science.
  • Ability to create relational data models.
  • Knowledge in deploying, productionizing, and scaling ETL solutions for real industrial use cases.
  • Regularly talk to internal stakeholders to ensure their information needs.
  • Partner closely with data analysts and scientists throughout the lifecycle of project. Ensure that necessary data is captured; analytic needs are well-defined up front and coordinate the analytic needs.
  • Knowhow of SCRUM-framework and tooling (DevOps, Jira).
• Strong analytical and problem-solving skills, with the ability to work independently and as part of a team.
• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Willing to learn and work in other task using numerical analysis techniques.

Preferred Qualifications:

• Familiarity with machine learning concepts and frameworks.
• Able to use other engineering numerical analysis methods (FEM, CFD etc.)
  
  

• 15+day annual leave
• Competitive salary, bonuses and allowances
• Career development in the Bosch group worldwide
• Top employer in mechanical engineer jobs and employee development policy.