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Strong brand, metro location, popular data role with broad toolset increases candidate competition.
Core data engineering skills transfer well, but specific ETL/platform tooling increases role specificity.
Multiple mandatory ETL/cloud tools and managerial leadership expectations raise filtering rigidity.
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Lead and mentor a team of data engineers to build scalable, reliable data systems and foster continuous improvement.
Design, develop, and maintain scalable data pipelines and architectures for OLAP and OLTP systems, including big data platform management (Hadoop, Hive).
Drive adoption and optimization of cloud-based data solutions (AWS), implement CI/CD pipelines, ensure data quality, governance, and security.
Mandatory skills: Python programming, data engineering tools including Ab Initio, Informatica PowerCenter, Oracle Data Integrator, SAP BODS, Matillion ETL, SnapLogic.
Experience managing large-scale data platforms and driving end-to-end data solutions.
Bachelor's degree in Business Analytics, Computer Science, or Statistics, or a Master's in Data Science.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in leading and mentoring data engineering teams with demonstrated leadership impact.
Skilled in managing and optimizing big data systems and cloud platforms, especially AWS.
Strong in cross-functional collaboration (data science, product, engineering) to deliver high-quality data solutions in a hybrid work environment.