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Tier-1 brand, metro location, and broad technical skillset increase candidate competition.
Role demands specialized data-platform and cloud experience, moderately limiting cross-industry transferability.
Explicit 8–10 years, management experience and specific data-stack skills enforce strict candidate filters.
Lead and mentor data engineering teams to build and optimize scalable data platforms and pipelines supporting business and data science functions.
Manage end-to-end project delivery ensuring timelines, quality, and alignment with business objectives.
Collaborate directly with analytics and business stakeholders to translate business needs into technical solutions and maintain platform performance.
8 to 10 years of data engineering experience including prior team management roles.
Proficiency in modern data stacks, both on-premises and cloud platforms (AWS/Azure).
Strong technical skills in SQL, Python, PySpark, database design, data modeling, and data governance.
Experience with Agile methodologies and project tracking tools such as Jira.
Experienced in leading and scaling engineering teams in complex data environments with strong technical credibility.
Comfortable managing cross-functional stakeholder relationships to align technical delivery with strategic business goals.
Proficient in architecting and tuning large-scale data ecosystems on cloud and on-prem platforms.