Singapore - Low Voltage Software Automation – Data Analyst
Tesla is seeking a versatile Data Analyst to join our Low Voltage Software Automation team.
Our team is at the heart of Low Voltage system. Microcontrollers, aka the brains in Tesla vehicles, control over 500 interfaces, which involve switches, sensors, cameras, and motors. We're responsible for developing software to communicate with and validate these microcontrollers.
As a Data Analyst in our team, you will play a crucial role in leveraging data to drive informed decisions, improve processes, and provide valuable insights to various Low Voltage engineering teams and products (Autopilot, Dojo, Optimus, and more…).
Responsibilities
- Dashboards: Build and maintain analytics tools and platforms that empower Low Voltage engineering teams to analyze and interpret data independently.
- Reports: Generate automated reports/alerts with relevant data insights for stakeholders.
- Collaboration: Collaborate with cross-functional teams to understand their data needs and provide data-driven solutions.
- Data Quality Assurance: Ensure data accuracy, integrity, and consistency across all data assets.
- Performance Monitoring: Monitor data pipelines and dashboards for performance and troubleshoot issues as needed.
- Documentation: Maintain clear and concise documentation of data processes, methodologies, and tools.
Qualifications
- Bachelor's degree in a relevant field (e.g., Computer Science, Data Science, Engineering).
- Proven experience as a Data Analyst or similar role.
- Strong proficiency in Python and libraries such as Pandas for data manipulation.
- Proficiency in SQL for data retrieval and analysis.
- Experience with database management and design.
- Familiarity with data visualization tools like Dash.
- Knowledge of ETL processes and tools like Apache Airflow.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration skills.
- Ability to work on multiple projects simultaneously.
Preferred Qualifications:
- Experience working with automotive manufacturing/engineering data or related fields.
- Knowledge of advanced statistical analysis and machine learning techniques.
- Familiarity with big data technologies and cloud platforms (e.g., AWS, Azure, GCP).
