Development engineer Automation & Scripting

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. 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. Required Qualifications: • Bachelors 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. 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.