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Tier-1 employer, common data-engineer title, mid-level experience, metro location, and broad toolset increase applicant competition.
Data engineering skills are broadly transferable across industries but some domain knowledge may be required.
Explicit minimum experience and degree requirement but flexible tool preferences create moderately strict filters.
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Design and build data infrastructure and systems for efficient data processing and analysis.
Develop and maintain data pipelines, integration, and transformation solutions using AWS, Azure Data Factory, Databricks, Apache Airflow, and Hadoop.
Collaborate with clients to understand data requirements and deliver actionable insights, ensuring data quality and security compliance.
Bachelor's degree required.
Minimum 2 years of relevant work experience.
Experience with cloud platforms (AWS or Microsoft Azure) and data engineering tools like Databricks, Apache Airflow, and Hadoop.
Travel flexibility up to 60%.
Background in Management Information Systems, Computer/Information Science, Systems/Electrical/Chemical/Industrial Engineering, Mathematics, or Statistics preferred.
Experienced in data architecture development, data modeling, and implementing data pipelines and integration strategies.
Comfortable navigating complex data environments and solving data-related challenges using advanced platforms and techniques.