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Capgemini
Overview:
We are seeking a highly motivated Data Analyst with strong technical and analytical skills to join our ADAS (Advanced Driver Assistance Systems) team. This role involves working with large-scale data from vehicle systems to drive insights, support data science initiatives, and contribute to the development of safer and smarter automotive technologies.
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Responsibilities:
• Perform data cleansing, aggregation, and analysis on large, complex datasets related to ADAS components and systems.
• Build, maintain, and update dashboards and data visualizations to communicate insights effectively (Power BI preferred).
• Develop and optimize data pipelines and ETL processes.
• Create and maintain technical documentation, including data catalogs and process documentation.
• Collaborate with cross-functional teams including data scientists, software engineers, and system engineers.
• Contribute actively to the internal data science community by sharing knowledge, tools, and best practices.
• Work independently on assigned projects, managing priorities and delivering results in a dynamic, unstructured environment.
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Required Qualifications:
• Bachelor’s degree or higher in Computer Science, Data Science, or a related field.
• Minimum 3 years of experience in the IT industry, with at least 2 years in data analytics or data engineering roles.
• Proficient in Python or Pyspark with solid software development fundamentals.
• Strong experience with SQL and relational databases.
• Hands-on experience with data science, data engineering, or machine learning techniques.
• Knowledge of data modeling, data warehousing concepts, and ETL processes.
• Familiarity with data visualization tools (Power BI preferred).
• Basic understanding of cloud platforms such as Azure or AWS.
• Fundamental knowledge of ADAS functionalities is a plus.
• Strong problem-solving skills, self-driven attitude, and the ability to manage projects independently.
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Preferred Skills:
• Experience in automotive data or working with sensor data (e.g., radar, lidar, cameras).
• Familiarity with agile development methodologies.
• Understanding of big data tools and platforms such as Databricks or Spark.
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