Finance Business Intelligence and Data Engineer
Employment Info
JOB DETAILS
Requirements
- You bring strong platform and data infrastructure experience, with a proven track record of scoping, tracking, and executing end-to-end data pipelines, tool implementations, or systems-level transformation roadmaps.
- You have a unique ability to see how platforms, integrations, data flows, and manual team workflows connect into a singular ecosystem. You easily spot where constraints in one area create bottlenecks across the whole P&L.
- You are highly proficient in data architecture (ideally with Snowflake or similar data lakes), data modeling, semantic layers, and custom integration layers with ERPs or financial planning tools (like NetSuite).
- You have a demonstrated history of utilizing practical AI/ML tools or predictive modeling workflows to turn unstructured or fragmented data into automated, highly reliable business solutions.
- You effortlessly bridge the gap between finance requirements, data engineering standards, and non-technical business leaders. You are comfortable challenging legacy manual habits and ad-hoc reporting loops to protect the core architectural roadmap.
Responsibilities
- Engineering a Financial Single Source of Truth: Designing intuitive data models and semantic layers in Snowflake to build a real-time, self-service 3-way reporting layer for our Board and Executive team.
- Building a Profitability Engine: Partnering with our Commercial and Supply Chain squads to build and systematize a P&L attribution model mapped to channels, markets, and products.
- Prototyping Predictive AI Tools: Collaborating with FP&A to deploy applied ML/AI techniques for automated cash and P&L forecasting, scenario modeling, and anomaly detection with robust human-in-the-loop controls.
- Evaluating Core Tooling: Leading the technical evaluation and reconfiguration/replacement assessment of our NetSuite Planning and Budgeting (NSPB) module and broader BI tool ecosystem.
- Driving Data Governance: Establishing auditable reconciliation frameworks between your new reporting layer and source systems to maintain total data trust, while codifying sustainable documentation for a seamless hand-off.
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