Description:

​HARMAN Automotive is hiring an entry-level to early-career Data Engineer for its core software and integrated technology platforms team in Bangalore. This unique role bridges foundational data engineering and the AI/ML ecosystem. You will design, maintain, and automate processing pipelines for structured and unstructured data, enabling features across in-vehicle infotainment, safety, and smart navigation. Working directly with data scientists, you will construct Extract, Transform, Load (ETL) routines, execute feature engineering, and optimize data workflows to integrate and validate PyTorch-based machine learning models for production model training and inference.

​Key Technologies:

​Python, SQL, PyTorch, Pandas, NumPy, Git

​Requirements:

• ​Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a closely related quantitative field.
• ​0–3 years of experience; freshers with strong academic records, capstone projects, or technical training in data pipelines are highly encouraged to apply.
• ​Strong foundational command over Python scripting for building data ingestion wrappers, automation macros, and system utilities.
• ​High proficiency using SQL to interact with relational databases or data warehouses, manage tables, and write complex queries to extract data sets.
• Practical baseline exposure using Pandas and NumPy libraries for data manipulation, file scrubbing, array operations, and data transformations.
• ​Foundational familiarity with PyTorch or similar deep learning frameworks (TensorFlow, Scikit-learn) to integrate modeling inputs into operational code channels.
• ​Sound grasp of data engineering architectures, including designing ETL pipelines, executing data pre-processing, feature engineering, and managing data quality validation checks.
• ​Strong understanding of foundational Computer Science principles, including data structures, basic algorithms, and version control repository mechanics using Git.
• ​Direct experience handling PyTorch inference loops, exposure to Big Data distributed engines (Apache Spark, Hadoop), basic knowledge of public cloud architectures (AWS, Azure, or GCP), or familiarity with data lakes.
• Quick learning agility, sharp logical problem-solving abilities, clear communication skills, and the capacity to collaborate within cross-functional teams with minimal supervision.