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Tier-1 brand plus mid-level data engineer title, broad GCP/Python skills, and likely metro location increases competition.
Strong data engineering fundamentals transfer across industries, but GCP and compliance needs increase specificity.
Explicit 6-8 years required plus specific GCP/Python/dashboarding skills make shortlisting strict.
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Design and scale complex, enterprise-level data infrastructure solutions, including ETL/ELT pipelines and automated data ingestion.
Own end-to-end orchestration and continuous tuning post-stabilization, ensuring system health and compliance with global legal standards.
Develop automated incident management frameworks and implement proactive data observability to reduce failures and optimize operational reliability.
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 dashboarding/visualization tools such as Lookerstudio, Data Studio, Tableau, or PowerBI.
Exceptional attention to detail with ability to follow detailed workflows independently and escalate issues appropriately.
Experienced in collaborating with stakeholders for strategic data architecture and security design.
Skilled at diagnosing architectural bottlenecks during system onboarding and knowledge transfer phases.
Capable of developing scalable, self-healing data systems with strong problem-solving and debugging expertise.