What are the responsibilities and job description for the GCP Data Engineer position at BRATHON?
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
2. 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)
3. 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