Senior Data Analyst

Role Overview

Senior Data Analyst (first hire for the function at Dave). You’ll build the reconciliation foundation for Dave’s data systems—designing pipelines, anomaly detection rules, and AI-powered matching logic to keep financial data trustworthy, audit-ready, and operationally reliable.

Key Responsibilities

• Build reconciliation infrastructure
  • Design and implement data pipelines reconciling transactions across internal systems (e.g., operations/ledger) and external partners (ACH networks, banking rails, payment processors).
  • Ensure “every dollar in equals every dollar out.”
• Lead anomaly detection & rules development
  • Create and maintain an anomaly rules library (timing differences, partial matches, unexpected delays, and true errors).
  • Evolve rules using ML-based signals as data matures.
• Implement AI-powered matching
  • Use probabilistic/fuzzy matching to resolve ambiguous or near-match transactions.
  • Reduce manual review queues and improve straight-through processing.
• Flag and triage unmatched records
  • Build real-time and batch pipelines to surface unmatched/delayed/anomalous transactions with enough context for fast resolution.
• Cross-functional technical leadership
  • Partner with Engineering (integration/pipeline reliability), Finance/Accounting (period-end close, audit support), and Reconciliation Operations (workflow tooling, exception handling).
• Define data quality standards
  • Create validation frameworks to separate expected timing lags from genuine discrepancies.
  • Document data contracts between upstream systems.
• Drive automation & process improvement
  • Reduce manual reconciliation work via scalable pipelines, alerting systems, and self-serve tooling.
• Elevate the team
  • Share best practices, mentor analysts, and help establish reconciliation/data quality as a core Analytics capability.

Requirements

• 5+ years in data analytics, data engineering, or financial data roles; ideally exposure to reconciliation, settlements, or financial operations.
• Strong SQL and Python (e.g., pandas, PySpark, or equivalent).
• Experience with Snowflake and/or Databricks (pipeline development, scheduling, data modeling).
• Familiarity with ACH transaction cycles / payment rails / financial operations.

Nice to Have

• Experience with dbt.