Staff Software Engineer, Data Platform - US (Remote)

10+ years of professional software engineering experience, including owning production systems end-to-end Significant experience working with data-intensive or distributed systems at scale Prior experience in a senior or staff/lead role influencing architecture, standards, and technical direction Strong programming skills in Python or Java, with experience building microservices and APIs Hands-on experience with Apache Kafka or similar event/messaging platforms Deep experience with Spark or Flink for large-scale data processing Deep experience with Airflow (or equivalent orchestration tools) Deep experience with Kubernetes for running data/compute workloads Strong SQL and data modeling skills; solid understanding of ETL/ELT patterns, data warehousing concepts, and performance tuning Experience building on AWS (preferred) or another major cloud provider Experience building or integrating AI agents into production workflows Familiarity with frameworks such as PydanticAI, LangGraph, Claude Code or similar Comfort working with logs, telemetry, and evaluation metrics to monitor, debug, and iteratively improve AI-driven systems Demonstrated ability to lead technical initiatives across teams Track record of mentoring other engineers and raising the bar on code quality, testing, and design Strong communication skills

Own end-to-end architecture for MLS and property data: streaming and batch pipelines, microservices, storage, APIs Design and evolve event-driven, Kafka-based data flows Drive technical design reviews and set engineering best practices Design, build, and operate backend services (Python or Java) exposing data via APIs/microservices Implement scalable data processing with Spark or Flink on EMR, orchestrated via Airflow, running on Kubernetes Champion observability and operational excellence for data and backend services Build and maintain high-volume, schema-evolving streaming and batch pipelines Ensure data quality, lineage, and governance are built into the platform Partner with analytics engineering and data science to make data discoverable Collaborate with ML/AI engineers to design and scale AI agents Work with frameworks such as PydanticAI, LangChain, or similar to integrate LLM-based agents Help define and implement evaluation, logging, and feedback loops for AI agents and data products Collaborate with Product, Engineering, and Operations to shape the data platform roadmap Translate business problems into technical strategies Mentor and unblock other engineers