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Tier-1 employer and metro location increase applicant density despite senior, specialized skill requirements.
Role demands deep data engineering, cloud and big-data skills making industry background highly relevant.
Explicit 12–17 years requirement and strong data engineering/cloud leadership requirements impose high strictness.
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Lead design, development, and implementation of data strategies and robust data platforms.
Architect and manage cloud-based data solutions, primarily leveraging AWS or similar platforms.
Mentor and guide a high-performing data engineering team to deliver optimized data pipelines and integration solutions.
Bachelor’s degree required.
12 to 17 years of relevant work experience in data engineering.
Proficient in Python, PySpark, SQL, and big data ETL performance tuning.
Experience with cloud platforms like AWS, Azure, or GCP for data engineering solutions.
Experienced leader capable of managing and mentoring data engineering teams in a global/virtual environment.
Strong strategic and operational expertise in cloud data architectures and cost optimization.
Ability to translate complex business requirements into scalable technical data solutions.