Data Engineer

• Design and build robust data pipelines and architectures on AWS or Azure
• ‍Develop and optimize ETL processes that handle large-scale structured and unstructured data from multiple sources
• ‍Work with distributed processing tools like PySpark and Pandas to move and transform data at scale
• ‍Use cloud services hands-on: Glue, Lakeformation, EMR for AWS Datafactory, Synapse, Datalake, Fabric on Azure
• ‍Model and warehouse data that feeds BI tools and supports real analytical decisions
• ‍Write clean Python or Scala to automate, integrate, and build
• ‍Collaborate with analytics and business teams to translate data needs into infrastructure that works
• ‍Contribute to tech stack decisions: your opinion on architecture matters here, not just your execution.

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