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Tier-1 brand, metro location, and popular mid-senior data engineering role increase competition.
Core data engineering skills are transferable, but Finance domain experience and Snowflake specialization raise specificity moderately.
Explicit 8+ years requirement plus mandatory Snowflake, ETL, and data engineering expertise makes screening stringent.
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Design, develop, and maintain scalable data pipelines, models, and products in Snowflake to support Finance reporting, analytics, and operations.
Partner with Finance BI Developers, Analytics, and engineering teams to build reliable, scalable, and governed Finance data solutions.
Drive adoption of data engineering best practices including modeling standards, testing, monitoring, documentation, and governance within Finance BI organization.
8+ years of experience in Data Engineering, Data Warehousing, or Analytics Engineering roles.
Expert-level proficiency with Snowflake and modern cloud data warehousing concepts.
Strong proficiency with SQL and experience with ETL/ELT pipelines and modern data engineering tools.
Bachelor's degree in Computer Science, Computer Engineering, or equivalent work experience; Master's degree desirable.
Experienced in supporting Finance, Sales Finance, Revenue Operations, or FP&A functions, preferably in subscription-based SaaS businesses.
Proven ability to lead technical projects that implement data quality controls, testing frameworks, and operational best practices.
Familiarity and working understanding of generative AI technologies and Large Language Models in relation to enterprise data products.