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Strong Tier-1 brand, generalist Data Engineer title, mid-level range, and broad skill requirements increase competition.
Core data engineering skills are portable but GCP and enterprise compliance raise some domain-specific sensitivity.
Explicit 6-8 years requirement and mandatory Python, SQL, and GCP skills increase shortlisting rigidity.
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Collaborate with stakeholders to define and implement scalable, secure, and resilient data architectures and access layers.
Design, build, and maintain high-performance ETL/ELT workflows and automated data ingestion pipelines with advanced visualization and impact measurement.
Own end-to-end data pipeline orchestration post-stabilization, including performance tuning, incident management automation, proactive observability, and compliance adherence.
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 Looker Studio, Data Studio, Tableau, or PowerBI.
Exceptional attention to detail and ability to independently execute complex, detailed workflows with escalation as necessary.
Experienced in collaborating across technical and business stakeholders to define data architecture and security in complex settings.
Skilled in designing automated incident management and data observability frameworks for system reliability.
Proven ability to architect and scale enterprise-grade data pipelines and maintain continuous operational ownership including global compliance.