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Tier-1 brand, metro location, and mid-level generalist data role drive high candidate competition.
Core data engineering skills transfer across industries, though finance domain experience is beneficial.
Mandatory 5+ years and expert Snowflake plus ETL requirements make filters strict.
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Design, develop, and maintain scalable data pipelines, models, and products within Snowflake to support Finance reporting, analytics, and operations.
Serve as primary data engineering partner to Finance BI Developers and stakeholders, translating business needs into scalable data solutions.
Drive adoption of data engineering best practices, including data modeling, testing, monitoring, documentation, governance, and operational excellence.
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.
5+ years of experience in Data Engineering, Data Warehousing, or Analytics Engineering roles.
Strong proficiency in SQL, experience with ETL/ELT pipelines, dimensional modeling, and data quality/testing frameworks.
Experienced in building enterprise-scale data products supporting Finance or related domains such as Sales Finance, Revenue Operations, or FP&A in subscription-based or SaaS businesses.
Familiar with BI platforms (e.g., Power BI, Tableau) and confident working with Finance stakeholders to deliver self-service analytics.
Demonstrates curiosity and working understanding of AI technologies, especially Large Language Models and AI-assisted development tools, to enhance data engineering solutions.