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.