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Strong brand, common mid-level data title, metro hiring, and broad cloud/SQL/Python requirements increase candidate competition.
Data engineering skills are transferable across industries but require domain tooling and cloud experience.
Mandatory 5+ years plus specific cloud, Python, SQL, DBT and DataOps experience raises screening strictness.
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Design and build robust, scalable data solutions and pipelines for analytics in a global data engineering environment.
Collaborate with business stakeholders to prioritize data engineering projects aligned with organizational goals.
Establish and promote best practices, efficient workflows, clear documentation, and data quality, reliability, lineage, and governance improvements.
Minimum 5+ years of experience in data engineering or related fields.
Proficiency in one or more programming languages such as Python, SQL, DBT.
Experience with at least one major cloud platform (AWS, GCP, or Azure).
Bachelor’s, Master’s, or PhD degree in Computer Science, Information Technology, Engineering, or related discipline.
Experienced in contributing across all stages of data engineering project delivery with leadership in technical design reviews.
Able to adapt quickly to evolving technologies and drive continuous improvement in data engineering practices.
Skilled in collaboration with cross-functional stakeholders to align data projects with business objectives in a globally distributed team environment.