Back
Mid-level, popular data role with specific PySpark/Databricks requirements increases applicant density.
Core big-data engineering skills (PySpark, Databricks) are broadly transferable across industries.
Explicit 2-5 years plus mandatory expert PySpark and Databricks technical requirements raise filter strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and analyze big data solutions using PySpark at an expert level.
Design and implement data processing workflows and visualizations using Databricks and Power BI.
Contribute to big data architecture with general knowledge of Spark, and potentially leverage beginner-level TensorFlow and PyTorch.
2-5 years of relevant work experience.
Expert-level proficiency in PySpark, Databricks, and Power BI.
Bachelor's or Master's degree in Engineering (B.E/B.Tech, M.E/M.Tech), MCA, or M.Sc.
Good to have knowledge of Java, Hadoop, SQL/Scala; automotive industry experience is preferred but not mandatory.
Experienced in big data analytics and engineering within a data-intensive environment.
Strong coding and tool expertise focused on PySpark and Databricks platforms.
Capability to contribute to automotive-related data projects with an understanding of big data frameworks and architectures.