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Tier-1 brand, common Data Engineer title, metro hiring, and broad skill requirements increase competition.
Core data engineering skills (ETL, SQL, Python, GCP) are easily transferable across industries.
Explicit 6–8 years plus mandatory GCP/Python/SQL and compliance obligations enforce strict screening.
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Design and scale complex data solutions including high-performance ETL/ELT pipelines and automated data ingestion layers to deliver business intelligence.
Collaborate with stakeholders to define data architecture, security, and scalability; conduct technical feasibility audits and system mapping for operational integration.
Own end-to-end data orchestration post-stabilization including performance tuning, system health, incident governance, and compliance with global legal standards.
6-8 years of experience building and maintaining enterprise-level data applications.
Bachelor's degree or equivalent practical experience.
Proficiency in Python, SQL, Google Cloud Platform (GCP), and data visualization/dashboard tools such as Lookerstudio, Data Studio, Tableau, or PowerBI.
Strong attention to detail and ability to follow detailed workflows independently.
Experienced in designing scalable, resilient data infrastructure with end-to-end ownership including incident management and compliance adherence.
Proficient in collaborative strategic planning and execution involving multiple internal stakeholders.
Demonstrates expertise in advanced data pipeline engineering and performance optimization in enterprise environments.