Data Engineer – Digital Transformation

Summary: The Data Engineer role focuses on developing cutting-edge data solutions that support transformation into a "Digital Enterprise" in the automotive industry. The primary objective is to collect, store, process, and analyze large sets of data to facilitate smarter decision-making and enhance service efficiency across various teams.

Main Responsibilities

• Collect, store, process, and analyze large data sets.
• Implement data solutions on Palantir Foundry or for specific AI solutions.
• Collaborate with global teams across development, manufacturing, quality, sales, and purchasing.
• Build large-scale batch and real-time data pipelines using frameworks like PySpark and Spark.
• Ensure data quality and perform data problem analysis.
• Develop, construct, test, and maintain data pipelines.
• Document data and maintain definitions.
• Contribute to functional analysis and user needs translation into structured data pipelines.
• Prepare data for predictive modeling and develop associated processes.
• Conduct feasibility studies for optimal technical solutions.
• Utilize Agile and DevOps methodologies to deliver projects timely.
• Share expertise and facilitate knowledge transfer within the team.

Key Requirements

• 3-5 years of experience in data mining from various data sources.
• Proven experience with data processing frameworks, particularly PySpark or Spark.
• Strong understanding of data quality assurance and analysis.
• Ability to develop and maintain data pipelines.
• Fluency in English, both verbally and in writing.

Nice to Have

• Bachelor's or Master's degree in computer science engineering.
• Experience with Big Data solutions and BI tools.
• Hands-on experience with PySpark/Python.
• Knowledge of PL/SQL or SQL.
• Familiarity with Agile Software Development methodologies.
• Excellent communication and documentation skills.
• Problem-solving and troubleshooting skills.
• Ability to create compelling narratives from data.