Data Analyst/Data Engineer (BQ / SQL / Python)

Role Summary

The Inventory & Demand Planning team is hiring a Data Analyst to scale a high-impact analytics roadmap across inventory, in-stock, supply, and forecasting. This role builds and maintains the data foundation that powers decision-making by translating business rules into reliable datasets, automating recurring KPI outputs, and supporting the ABC/XYZ + lifecycle governance framework so leaders and merchants operate from consistent, auditable numbers with minimal manual effort.

This is a hands-on analytics engineering role centered on data pipelines, automation, and metric integrity to enable planning decisions and streamline reporting/governance outputs. The analyst will partner closely with Inventory Planning leadership to implement definitions, validations, and scalable reporting.

What You’ll Work On

• Build and maintain curated BigQuery tables/views that standardize inventory, demand, availability, open POs/in-transit, backorders, and KPI feeds.
• Write clean, performant SQL that powers weekly/monthly reporting and executive dashboards.
• Automate refreshes and reduce manual effort through validations, reconciliations, exception flags, and clear documentation.
• Support ABC/XYZ roadmap execution by producing required inputs/outputs, applying multiplier logic, and keeping the classification pipeline stable and easy to audit.
• Support forecasting improvements using Python (data prep, feature engineering, back-testing, evaluation) and help operationalize outputs into cadence reporting.
• Expand datasets with additional signals where available (promo flags/types, merchandising tags, launch/NPA indicators, traffic/CVR signals, marketing calendar attributes).
• Partner with Merchandising, Marketing Ops, Finance, and BI/IT to align definitions, improve data quality, and drive adoption of standardized metrics.

How Success Will Be Measured

• KPI tables and dashboard feeds refresh reliably with minimal manual intervention.
• Faster turnaround on leadership and merchant requests with consistent, traceable metric logic.
• ABC/XYZ outputs are accurate, on-time, and easy to maintain.
• Forecast inputs improve through better data structure and added business/marketing signals.
• Documentation and change control keep datasets stable as business rules evolve.

Required Qualifications

• 3–5 years in analytics/data roles (retail/e-commerce strongly preferred).
• Strong SQL and hands-on experience with BigQuery (or similar cloud warehouse).
• Working Python proficiency for analysis/automation (pandas/NumPy).
• Experience supporting BI dashboards and recurring reporting.
• Demonstrated ability to validate and reconcile metrics across sources, troubleshoot discrepancies, and document logic clearly.
• Strong problem-solving, attention to detail, and clear communication with business stakeholders.

Preferred Qualifications

• Familiarity with ML/forecasting workflows (feature engineering, evaluation, operationalizing outputs) to support forecasting and driver-based models in partnership with the team.
• Familiarity with Looker/LookML (or similar semantic layers).
• Exposure to dbt and/or orchestration tools (Airflow/Composer or equivalents).
• Comfort with inventory/planning concepts (WOS, aging, availability, lost demand, backorders) and classification/ranking approaches (ABC/XYZ, PFEP).
• Version control (Git) and basic engineering hygiene (testing, documentation, change logs).

Tools / Environment

BigQuery, SQL, Python, Looker, Jira/Confluence (or equivalent), Google Cloud tooling as applicable.