GCP Data Engineer

Job Title: GCP Data Engineer Location: Phoenix, AZ (Hybrid) Job Type: Contract Long Term 1. Business Division & Project Summary Business Division: Enterprise Business Intelligence (EBI) – AMEX Position supports AMEX’s Enterprise Business Intelligence (EBI) organization, specifically the Experience Analytics (XP) team. This division focuses on: • Marketing analytics and campaign intelligence • Building data pipelines, ETL processes, and insight delivery mechanisms • Delivering insights for: • AMEX‑initiated campaigns • Merchant‑partner campaigns • Campaign creative journeys & customer experience pathways • Enabling multiple reporting/insight delivery channels: • Dashboards (Tableau) • API‑based insights • Report distribution • Audio‑layer reporting (narrative insights) • Project Summary (New Workload Coming) A new upcoming initiative is driving the need for hiring. The details are not confirmed yet, but likely include: • Creation of a completely new data pipeline • Development of new visualization/reporting layers for this pipeline • Work within GCP ecosystem — BigQuery, Cloud Composer, DataProc, Spark, Python 1. Role Summary & Responsibilities The requirement is a hybrid role combining: A. Data Engineering (Primary – ~60–70%) Key responsibilities: • Build and maintain ETL pipelines • Work within AMEX’s GCP ecosystem: • BigQuery (primary analytics database) • Cloud Composer (orchestration) • DataProc (Spark/Python‑based ETL jobs) • Data curation, aggregation, and transformation (SQL-heavy) • Potential work with PySpark depending on pipeline design • Implement AI‑powered data quality checks (future roadmap) • Contribute to domain-specific datasets (marketing analytics) Tech stack mentioned: • Python • PySpark • SQL • BigQuery • GCP (Composer, DataProc) B. Data Visualization / BI Engineering (~30–40%) Responsibilities: • Build dashboards for marketing analytics • Visualize campaign journeys, insights & trends • Use Tableau primarily (Power BI is deprioritized) • Support multiple insight delivery formats: • Dashboards • API-based insight delivery • Narrative/Audio insights • Convert analytical output into consumable business insights Tools: • Tableau • (Optional) Power BI • APIs (for insight publishing) 1. Expectations & Role Fit Criteria A. Core Expectations • Strong data engineering foundation • Strong SQL and BigQuery experience • Hands-on with Tableau • GCP ecosystem familiarity (mandatory) • Ability to manage both data pipelines & visualization layers • Prior exposure to ETL, Spark, or Python desirable - AI/ML experience B. Soft Skills • Ability to collaborate with global teams (India + US) • Strong communication for requirements gathering • Independence in handling end‑to‑end data + BI workflows