Data Engineer responsible for designing, developing, and maintaining data pipelines. Performing comprehensive data analysis and creating visualizations to support predictive range management activities.
Responsibilities
Design and implement robust data pipelines using Python and Databricks platform
Perform data extraction, transformation, and loading (ETL) operations on large datasets
Conduct thorough data analysis, cleaning, and transformation to ensure data quality and integrity
Create compelling data visualizations and reports to communicate insights to stakeholders
Collaborate with cross-functional teams using Git for version control and code collaboration
Develop and maintain scalable data processing solutions using pandas and numpy libraries
Optimize data workflows and improve processing efficiency
Document data processes, methodologies, and findings
Requirements
Minimum BE / BTech in Electrical/ Electronics/ Computer Science/ related disciplines
Strong Python Programming: Proficiency in Python with hands-on experience in data-related projects
Databricks Platform: Experience working with Databricks for big data processing and analytics
Version Control: Solid understanding and practical experience with Git for code management
Data Processing: Expertise in data analysis, transformation, and cleaning techniques
Data Visualization: Ability to create meaningful visualizations and dashboards
Python Libraries: Strong proficiency in pandas and numpy for data manipulation and analysis
Azure DevOps: Experience with Azure Web App deployment and CI/CD pipelines (Good-to-Have)
Rust Programming: Knowledge of Rust programming language is a plus (Good-to-Have)
Physics & Engineering Analytics: Experience with physics-based computational modeling including force dynamics, power calculations, and energy analysis (Good-to-Have)
Automotive Domain Knowledge: Understanding of conventional Internal Combustion Engine (ICE) systems and electric vehicle technologies (Good-to-Have)
Experience with cloud platforms (preferably Azure) (Good-to-Have)
Knowledge of SQL and database management (Good-to-Have)
Familiarity with machine learning concepts (Good-to-Have)
Experience with other data visualization tools (Tableau, Power BI, etc.) (Good-to-Have)
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