Data Engineer (Finance)

Avetta is a SaaS platform that connects leading organizations with qualified suppliers, contractors, and vendors. The Data Engineer (Finance) will collaborate with various teams to drive insights that influence executive decisions and optimize complex revenue analytics and planning processes.

Responsibilities:

• Raise the Company’s FP&A Cash Billings analytics & reporting function by optimizing:
• Trace and join invoicing and customer-activity events end-to-end using clear, testable logic
• Design and build out an analytically-derived “Connection Subscription Ledger”: a detailed, time-aware log of monetized (billable) client–supplier connections, morphing into a handoff-ready dataset that Corporate BI productionizes in Snowflake
• Build analytics-ready warehouse models (SQL + modeling):
• Write high-performance SQL to create curated tables/views that support:
• Cohort creation and retention (by activation/event timing)
• Expansion/contraction and product mix shifts
• Renewal behavior and customer lifecycle segmentation
• Price lift measurement and attribution
• Churn classification and event-driven “bridge” logic
• Establish foundational tables with carefully chosen and clearly defined data grain, durable surrogate/primary keys, and consistent dimensional attributes
• Bring data modeling rigor into Finance reporting:
• Translate finance requirements into data logic: partner with the Business Analyst to define rules, acceptance criteria, and edge-case handling
• Run tight iteration loops: prototype → validation protocols → refine → document → finalize
• Provide “definition control” so recurring reporting stays consistent month-over-month
• Foster a wholistic understanding of the business (including underlying drivers and relationship/impact) within and across the entire FP&A team, leading to improved processes, collaboration, insight generation and optimal business outcomes
• Develop and monitor business performance indicators, highlighting trends, opportunities for improvement, causes of unexpected variance, and partner with finance and business partners to optimize downstream actions

Requirements:

• Bachelor's Degree in relevant field; additional education/certification is a plus
• 2–5 years of experience in data engineering / analytics engineering / advanced analytics roles in Snowflake or other modern cloud data warehouse
• Strong SQL (complex joins, window functions, incremental logic, recursive query development, performance tuning), with proven ability to model data for analytics (facts/dimensions, grain, keys, cohort logic)
• 1 year of experience supporting dbt-style modular SQL, testing, and documentation
• Proficiency in AI-based tech stack solutions, agent design or company-specific LLM tooling