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Tier-1 brand, metro location, generalist data engineer role with common tech stack increases candidate competition.
Core data engineering skills (SQL, Python, PySpark, cloud) are broadly transferable across industries.
Explicit 6-8 years requirement, managerial experience, and mandatory tech stack make filtering strict.
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Lead and oversee the full data engineering development lifecycle ensuring timely delivery and alignment with business objectives.
Manage project risks and quality control to maintain team productivity and project standards.
Collaborate closely with analytics and business stakeholders to translate business needs into technical plans and data products.
6 to 8 years of experience in data engineering including previous team management experience.
Proficient in modern data stack technologies on-prem and cloud platforms (AWS/Azure).
Strong technical skills in SQL, Python, PySpark, database design, data modeling, data management, and data governance.
Experience with Agile methodologies, Scrum, and project management tools like Jira.
Experienced in managing data engineering teams and delivering complex, scalable data platforms and pipelines.
Strong operational focus on project delivery, risk management, and stakeholder communication within analytics and business contexts.
Technically strong in cloud-based data engineering solutions and capable of bridging data engineering with data science for business impact.