Staff Software Engineer (Python) United States

About the Role

Own the data infrastructure that powers real-time pricing decisions for thousands of hotels worldwide in an engineering culture where AI is how work gets done today. As the technical authority on Duetto's data lakehouse, you'll drive pipeline architecture, data quality, and the shift from batch to near-real-time streaming.

About Duetto

Duetto is the hospitality industry's leading revenue management platform, founded in 2012 by former Wynn Resorts executives. We built the world's first Revenue & Profit Operating System—a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance, and more) that provides hotels, resorts, and casinos a complete picture of their revenue and profitability. Trusted by clients ranging from independent boutique hotels to global chains, Duetto has been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we're accelerating our investment in AI while maintaining a genuine passion for the industry we serve.

Responsibilities

• Own the design, performance, and reliability of Duetto's data lakehouse, evolving the Python/PySpark pipeline framework across a bronze → silver → gold architecture on AWS (Glue jobs, Iceberg MERGE operations, schema evolution, and partitioning strategies).
• Architect the shift from batch to near-real-time streaming, building SQS-driven stream pipelines with Iceberg sinks and expanding ingestion, normalization, and analytics layers across the full lakehouse.
• Drive data quality and governance at scale by extending the Great Expectations framework, leading adoption of data contracts to formalize schemas between producers and consumers, and owning the Athena SQL layer that analysts and product teams depend on.
• Strengthen observability and reliability through Datadog, Sentry, and Sumo Logic, while optimizing Glue job performance (worker sizing, DPU allocation, Spark tuning, and cost management).
• Build and maintain shared internal Python libraries published to JFrog, and drive improvements to GitHub Actions, Docker-based testing, and CI/CD deployment workflows.
• Work AI-first daily, using Claude Code and MCP tools in your regular workflow, and contribute to AI-assisted pipeline generation, schema inference, and automated data quality alongside a custom multi-agent system with 17 specialized agents.

Requirements

• 7+ years building production data systems in Python.
• Deep expertise in PySpark and distributed data processing (Glue, EMR, or Databricks).
• Strong experience with lakehouse architectures: Iceberg, Delta Lake, or Hudi on S3.
• Production experience with Airflow or a comparable workflow orchestrator.
• Solid AWS production experience across S3, Glue, Athena, Lambda, and SQS.
• A track record of improving data quality, governance, and pipeline reliability at scale.

Nice to Have

• Working knowledge of Java for reading upstream systems.
• Experience with Trino or Presto for interactive SQL analytics at scale.
• Experience with dbt for data transformation and modeling.
• Familiarity with Great Expectations or similar data quality frameworks.
• Genuine interest in AI-assisted development and LLM-based tooling.
• Familiarity with hospitality data (reservations, rates, inventory, demand signals).

Why Duetto?

• AI-first engineering: Every engineer uses Claude Code and a custom multi-agent system daily. Contribute to AI-assisted pipeline generation and work alongside 17 specialized agents with human-in-the-loop approval gates.
• Real technical challenge: Millions of rate decisions processed daily, 80+ integration partners, and a live evolution from batch to near-real-time streaming.
• Ownership: This Staff-level role grants true technical authority over the lakehouse that powers every pricing decision, forecast, and report in the product.
• Team culture: Low ego, high EQ, genuine intellectual curiosity, and active mentorship in a collaborative US and Europe team.
• Modern stack at scale: Python/PySpark, Apache Iceberg, Airflow, AWS Glue, SageMaker, Terraform—tools selected for the problem, not the press release.

Location: Remote (US)