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familiarity with software engineering hiring pipelines, data/AI role taxonomies, and cybersecurity certification pathways (e.g., CompTIA, CISSP, cloud certifications). Experience working with or advising
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, data/AI role taxonomies, and cybersecurity certification pathways (e.g., CompTIA, CISSP, cloud certifications). Experience working with or advising students or early-career professionals in technical
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business units, technical teams, and executive stakeholders. Demonstrated success delivering enterprise-level technology projects (e.g., CRM, ERP, infrastructure, cloud systems). Proven ability to lead
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in database systems, including: Relational databases (e.g., PostgreSQL / SQL) Graph databases (e.g., Neo4j, Memgraph, or equivalent) Familiarity with cloud computing environments (e.g., Azure, AWS
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., PostgreSQL / SQL) Graph databases (e.g., Neo4j, Memgraph, or equivalent) Familiarity with cloud computing environments (e.g., Azure, AWS, or GovCloud equivalents), including containerized or scalable ML
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units, technical teams, and executive stakeholders. Demonstrated success delivering enterprise-level technology projects (e.g., CRM, ERP, infrastructure, cloud systems). Proven ability to lead diverse
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Qualifications Education: Bachelor's degree in Information Systems, Computer Science, Engineering, or a related field required Experience: 4–6+ years of experience building cloud-native data pipelines
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, enterprise data modeling, or data engineering. Proven experience modernizing legacy data environments and designing cloud-native, AI-ready data architectures. Experience working with large, complex enterprise
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(e.g., Neo4j, Memgraph, or equivalent) Familiarity with cloud computing environments (e.g., Azure, AWS, or GovCloud equivalents), including containerized or scalable ML workflows. Strong software
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of database systems, including: Relational databases (e.g., PostgreSQL / SQL) Exposure to graph databases (e.g., Neo4j, Memgraph, or similar) Familiarity with cloud computing environments (e.g., Azure, AWS