Sr. Data Engineer / Quality Engineering

Tesla
April 08, 2023
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Offerd Salary:Negotiation
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Contract Type:Other
Working Time:Negotigation
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What to Expect

Tesla's mission is to accelerate the world's transition to sustainable energy. We are committed to hiring the world's best and brightest people to help make this future a reality.

What You'll Do

  • Automating analyses and authoring pipelines using SQL, Python, Airflow, Kubernetes based ETL framework
  • Maintaining existing data visualizations, data pipelines and dashboard enhancement requests
  • Work effectively with engineers and conducting end-to-end analyses, from data requirement gathering, to data processing and visualization using Tableau
  • Acquire data from primary or secondary data sources and maintain databases/data systems to empower operational and exploratory analysis
  • Monitoring key product metrics, understanding root causes of changes in metrics
  • Identify, analyze, and interpret trends or patterns in complex data sets and depict the story via dashboards and reports
  • Perform data quality validations to ensure data creation is as per the business needs and expectations
  • Work with management to prioritize business and information needs
  • Follow best practices for scalability and performance, ensuring data quality, and maintaining documentation.
  • Collaborate with other team members for effective knowledge transfers.
  • What You'll Bring

  • Minimum of 2-3 years of experience in a data engineering/software related capacity
  • Proficient at ad-hoc analysis using SQL queries and python data analysis packages (e.g. Pandas, Numpy)
  • Understanding of relational database theory and proficiency in writing, understanding, and optimizing complex SQL code
  • Experience with Business Intelligence tools (e.g. Tableau) and real time dashboard development
  • Software engineering fundamentals, knowledge of data structure and algorithms
  • Strong communication, organizational, and analytical and problem-solving skills
  • Preferred: BS/MS in Management Information Systems, Computer Science, Engineering, Statistics, or another technical field
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