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Mid-level data platform role, metro location, broad skills requirement increases applicant competition.
Core data engineering and cloud skills are highly transferable across industries, low domain-specific lock-in.
Explicit 7+ years, mandatory data architecture and cloud experience, strong tech-stack requirements.
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Lead the design and architecture of end-to-end scalable data platform solutions using cloud technologies (AWS, Azure, GCP) including data lakes, warehouses, ETL/ELT pipelines, and real-time streaming.
Define and drive the long-term data platform strategy and roadmap, including migration and modernization of legacy systems to cloud/hybrid architectures.
Provide technical leadership, oversee solution delivery, collaborate cross-functionally, and ensure data governance, security, and compliance with standards like GDPR and HIPAA.
Bachelor’s or Master’s degree in Computer Science, Engineering, IT, or related field.
Minimum 7+ years of experience in data architecture, data engineering, or similar role focused on designing large-scale data platforms.
Proven experience architecting cloud-based data solutions (data lakes, warehouses, ETL pipelines) on Azure, AWS, or GCP.
Strong knowledge of data modelling, governance, security, cloud-native data technologies, and regulatory compliance (e.g., GDPR, HIPAA).
Experienced in leading cloud migration and modernization projects for large-scale data systems with a strategic mindset balancing business and technical needs.
Demonstrates expertise in performance optimization, scalability, and advanced data integration techniques including real-time streaming and batch processing.
Skilled in leading technical teams, mentoring, and fostering collaboration across data engineering, data science, and business teams in fast-paced environments.