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Tier-1 brand and metro location increase candidate density despite senior specialization.
Core data engineering skills are transferable but Finance domain and Snowflake expertise increase specificity.
Explicit 8+ years requirement, expert Snowflake and enterprise data skills create stringent filtering.
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Design, develop, and maintain scalable data pipelines, models, and products within Snowflake for Finance reporting, analytics, and operations.
Partner with Finance BI Developers and stakeholders to translate business requirements into scalable data engineering solutions.
Lead adoption of data engineering best practices including data modeling standards, testing, monitoring, documentation, governance, and operational excellence.
8+ years experience in Data Engineering, Data Warehousing, or Analytics Engineering roles.
Expert-level proficiency with Snowflake and modern cloud data warehousing concepts.
Bachelor’s degree in Computer Science, Computer Engineering, or equivalent; Master’s degree desirable.
Strong proficiency with SQL and experience with data engineering tools for orchestration, transformation, and automation.
Experienced in supporting Finance, Sales Finance, Revenue Operations or FP&A in subscription-based software or SaaS business contexts.
Technical lead experience managing complex data engineering projects and stakeholder expectations.
Familiarity with generative AI technologies and Large Language Models, with a working understanding of AI tools impacting enterprise data engineering.