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Tier-1 brand, mid-level generalist role with broad skills in a metro makes competition high.
Requires data product and Salesforce ecosystem experience, moderately limiting cross-industry transferability.
Explicit 5–8 years plus Snowflake, Python, BI, governance and leadership requirements make shortlisting strict.
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Own the development of canonical, single-source-of-truth data assets supporting Customer Success teams such as Customer Support, Digital Success, Training, Certifications, Success Guides, and Architects.
Build and scale self-serve data capabilities enabling users to access and act on trusted data with minimal friction.
Collaborate with leadership and cross-functional data teams to prioritize data product opportunities that improve decision-making, automate workflows, and measure impact via defined success metrics.
Bachelor’s or Master’s degree in Computer Science, AI, Information Technology, or related field.
5-8 years of experience as Data Analytics and BI Engineer or in product management for data-related roles.
Strong proficiency in advanced SQL (Snowflake), Python, Tableau, version control (Git), and CI/CD pipelines for production deployment.
Experience with Salesforce ecosystem and knowledge of data governance including GDPR/CCPA compliance.
Experienced in leading data product strategy and execution in large, complex enterprises with multiple stakeholder groups, including C-suite engagement.
Skilled in translating complex AI and data analysis into actionable engineering solutions and predictive tools, with strong statistical literacy.
Able to operate strategically and tactically in fast-paced, ambiguous environments, balancing long-term vision with agile delivery and cross-functional collaboration.