Data Engineer Cloud

Must have: 

The role: Data Architect on Hyatt''s growing data engineering team, reporting into a fairly new, high-visibility group. You''d work closely with data engineering, data science, and data product management to shape how data flows across the company.

Core responsibilities:

• Own the enterprise data architecture strategy — setting standards for data flow, aggregation, migration, modeling, and consumption
• Bridge business and engineering — gather requirements from stakeholders (agile teams, people data, project portfolios) and translate them into technical specs for ETL/BI developers
• Design end-to-end data pipelines — from data lake/warehouse architecture through security review and deployment
• Governance — validate that projects align with target-state architecture, enforce data quality standards, handle prioritization/cost-benefit tradeoffs across competing stakeholder demands
• Reporting infrastructure — help build self-service and automated reporting for leadership/execs

What they want in a candidate:

• 6+ years in data engineering/BI/analytics, with 4+ years specifically in architecture for commercial-scale pipelines
• Strong cloud exposure (AWS preferred)
• Hands-on familiarity with BI tools (Tableau, PowerBI, Looker, ThoughtSpot)
• Knowledge of data warehouse/lake platforms (Snowflake, Redshift, SQL Server)
• Bonus: big-data/open-source stack experience (Spark, Kafka, Hadoop, HBase, Elasticsearch)
• Comfortable with a range of databases (SQL, Python, PostgreSQL, MongoDB, Oracle, etc.)
• A bachelor''s in a quantitative field (CS, engineering, math, stats, finance); an advanced degree is a plus
• Soft skills matter a lot here too — they explicitly want someone who''s a strong relationship-builder, comfortable with ambiguity, and aligned with Hyatt''s stated values (respect, integrity, humility, empathy, creativity, fun)

In short: this isn''t a pure "build pipelines" engineering role — it''s a strategic, cross-functional architecture position where technical depth (pipelines, cloud, BI, big data) matters, but so does the ability to influence stakeholders, set standards, and prioritize across a chaotic, fast-moving environment.