Sr. Data Engineer - US (Remote)

About the role

The Sr. Data Engineer will play a pivotal role in transforming the platform architecture and driving AI-powered product delivery at Luxury Presence. This role requires a deep understanding of data engineering, strong technical leadership, and a passion for using AI to enhance data operations.

Responsibilities

• Build and scale high-throughput streaming pipelines using Airflow, Spark Streaming, Kafka, and Iceberg.
• Design, implement, and operate pipelines ingesting 400M+ monthly MLS updates across 350+ integrations.
• Model and deliver high-quality, production-grade real estate datasets.
• Develop and maintain datasets that power core product experiences, focusing on data modeling, transformation logic, and balancing freshness, accuracy, and cost.
• Strengthen data quality and observability by implementing and improving data quality checks, monitoring, and alerting.
• Leverage AI to improve data operations by contributing to AI-driven tooling that helps triage, debug, and resolve data quality issues.

Requirements

Attributes:

• Already build with AI daily.
• Strong opinions about how AI changes software architecture, team structure, and engineering culture.
• Think in systems and connect technical decisions to customer outcomes and long-term business value.
• Communicate clearly and directly, explaining complex tradeoffs to product, design, and executive stakeholders.
• Energetic and comfortable with ambiguity and speed in a fast-growing company.
• Like to have fun at work and enjoy building together.

Skills and Experience

• 6+ years of professional data engineering or software engineering experience.
• Strong experience with distributed data processing and streaming systems (Spark / PySpark, Kafka).
• Proficiency in Python (Pydantic preferred) and familiarity with Node/TypeScript.
• Experience building and maintaining data pipelines on AWS using tools like Airflow, Spark Streaming, and Iceberg.
• Solid understanding of data modeling and working with large-scale datasets.
• Familiarity with event-driven systems and ingestion patterns (Kafka, SQS).
• Experience implementing data quality checks, monitoring, and debugging data issues.
• Interest in applying AI/ML or automation to improve data workflows.
• Proven track record leading high-impact initiatives from concept through production in a SaaS environment.
• Expert-level grasp of software design principles and experience with multi-tenant platform architectures.