Data Engineer

1 week ago

Toa Payoh, Singapore Tesla Full time

What to Expect
- Tesla Electronics Test and Automation Group (ETAG) is the main point of contact to ensure the highest quality vehicle, silicon and robotics electronics for our customers. Our mission is to develop test automation equipment, architect software automation framework, and provide hardware/software/data infrastructure for Tesla electronics communities worldwide.

We are seeking a highly motivated and experienced data engineer who would be responsible for deriving analytical insights from data to optimize production yield. This role will work in cross-functional environment driving data-driven decision-making
- builds metrics, owns the data pipelines and reporting for capacity expansion at scale.

What You’ll Do
- Analyze manufacturing, equipment and vehicle data and extract useful statistics and insights about failures in order to drive meaningful improvements to production quality and customer experience.
- Work effectively with engineers and conducting end-to-end analyses, from data requirement gathering, to data processing and modeling
- Interpret data, analyze results using statistical techniques and provide ongoing reports
- Acquire data from primary or secondary data sources and maintain databases/data systems to empower operational and exploratory analysis
- Maintaining existing and develop new data visualizations, data pipelines and dashboard enhancement requests
- Automating analyses and authoring pipelines using SQL, Python, Airflow, Kubernetes based ETL framework
- Perform data quality validations to ensure data creation is as per the business needs and expectations

What You’ll Bring
- Strong knowledge of Python, SQL and experience with multiple data architecture paradigms (MySQL, kafka, Spark)
- Strong knowledge of data visualization techniques and tools using Tableau, Power BI, Matplotlib, Plotly etc.
- Strong knowledge of data warehousing concepts, data mining tools and techniques
- Able to work under pressure while collaborating and managing competing demands with tight deadlines
- Understanding of various statistical techniques preferred
- Knowledge of manufacturing and service operations preferred
- Familiar with Docker, Kubernetes and basic knowledge of DevOps concepts and storage solutions
- Experience with creating automatic data pipelines, scheduling tools (cronjobs, Airflow, Kubeflow etc.)

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