Trinity Industries is seeking a Data Management Engineer in our Queretaro, MX Office.
The successful candidate will be part of our Dallas, TX Corporate Enterprise Data Engineering team. The engineer will have professional experience in data integration, data transformation, and developing data pipelines.
What you'll do:Design data models and data storage solutions in the cloud (e.g., AWS, Azure, GCP).Proficiency in programming languages commonly used in data engineering, such as Python, Java, or Scala.Build processes supporting data transformation, data structures, metadata, dependency, and workload management.Experience with API based data acquisition and management.Experience with data storage and processing technologies (e.g., Hadoop, Spark, Kafka, SQL databases).Work with data scientists to facilitate technical design of complex data sourcing, transformation, and aggregation logic, ensuring business analytics requirements are met.Work with big data pipelines to develop streaming analytics.Utilize business intelligence data visualization tools and techniques to translate business analytics into solutions.Experience and familiarity with parallel processing/multithreading and compute optimization.Must possess effective communication skills, both verbal and written.Strong organizational, time management, and multi-tasking skills.Work with management to prioritize business and information needs.What you'll need:Bachelors or equivalent with a minimum of 5 years of relevant experience.Proficiency in programming languages relevant to data engineering, including Python, Java, or Scala.Deep understanding of data modeling.Must be fully fluent in both English and Spanish (conversationally and written).Strong experience with cloud-based data solutions, especially AWS, Azure, and GCP.Familiarity with parallel processing, multithreading, and compute optimization.Nice to have:Experience with Databricks or Palantir Foundry software deployment is a plus.Expertise in designing cloud solutions across platforms like Azure, AWS, and Google.
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